QUADTREE-STRUCTURED WALSH TRANSFORM CODING

Abstract: Two dimensional data structures are represented by quadtree codes with embedded Walsh transform coefficients. The quadtree code permits both variable block size inherent in quadtrees, and the calculational simplicity of Walsh transform descriptions of nearly uniform blocks of data. Construction of the quadtree is calculationally simple for implementation in a digital system which does a bottom-up determination of the quadtree because Walsh transform coefficients and a measure of the distortion can be recursively calculated using only Walsh transform coefficients from the previous level in the quadtree. Uniform step size quantization, which is optimal for variable length coding and generalized gaussian distributions, permits fast encoding and decoding of quadtree code.

Description: QU ADTREE-STRUCTURED WALSH TRANSFORM CODING BACKGROUND OF THE INVENTION Field of the Invention This invention relates to methods and circuits tor transmuting and storing information that is two dunensionally related and in particular relates to transmitting and stonng digital information using a quadtree code with embedded Walsh transform coefficients. Description of Related Art Many two dimensional data structures are used in digital systems. A common example is a pixel map. Pixel maps are commonly used m video displays and in printer to descnbe a image being generated. With a pixel map. the color or intensity of each pixel is indicated by a corresponding datum in the pixel map. Pixel maps have rows and columns of data corresponding to the rows and columns of pixels on a video display and can include thousands or millions of data. For example, a standard VGA video display is 640 pixels wide and 480 pixels high and contains 307,200 pixels. A pixel map represenung a two color image which fills a VGA display contains at least 307,200 bits of data, one bit for each pixel. For 256 colors or shades or grey, eight bits of data are required per pixel, and the pixel map contains at least 307,200 bytes. Because of the large number of pixels in a video image, pixel maps can require long times to transmit and large amounts of memory to store. Encoding techniques exist for efficiently transmitting or storing two dimensional data structures without using pixel maps. One such technique uses quadtrees to describe images. A quadtree is a collection of nodes organized in levels and connected by branches. Each node in a quadtree structure has four branches connecting the node to four higher level nodes unless the node is a leaf node. Leaf nodes have no branches to higher levels. For a two color image, each leaf node in the quadtree has a value which describes the color a particular area in the image. The level 0 node represents a block containing the entire image and is 1 if the image contains a foreground color and 0 if the image only contains a background color. A level 0 quadtree accurately represents only single color images. Nodes in higher levels of a quadtree correspond to sub-blocks of blocks described in preceding levels, and typically, more levels provide a more accurate quadtree representation of the image. Fig. 1 A shows a two color image having a foreground color region 100. Fig. IB shows a quadtree which describes an approximation of the image of Fig. 1A. Fig. 1C shows blocks conesponding to the nodes of the quadtree of Fig. IB. Level 1 of the quadtree corresponds to a partiϋon which divides the image into four blocks 1 10, 120. 130, and 140 Block 120 contains only the background color and has node value zero. Blocks 1 10, 130, and 140 have node value one indicating at least a poruon of blocks 110, 130, and 140 contains the foreground color. In Fig. IB, level 1 nodes are 101 1 using the convention that the top left block is the left-most branch, the top right block is the second branch from the left, bottom left block is the third, and bottom πght block is the furthest πght A level 1 quadtree descnption of Fig. 1 A replaces block 120 with the background color and each of blocks 110, 130, and 140 with the foreground color. For level 2, blocks 1 10, 130, and 140 are divided into three sets of four sub-blocks 111-114, 131-134, and 141-144. Block 120 is not further divided because the level 1 descnption of block 120 accurately represents the constant background color of block 120. At level 2, blocks 1 13, 114, 131, 132, and 141 contain the foreground color and have node value one. Blocks 111, 112, 133, 134, and 142-144 contain only the background color and have node value zero. The quadtree of Fig. IB is expanded to level 2 by adding four new nodes and four new branches to each non-zero node of level 1. The level 2 quadtree of Fig. IB approximates the image by filing blocks 113, 1 14, 131, 132, and 141 with the foreground color and filing blocks 111, 112, 120, 133, 134, and 142-144 with the background color. The level 2 quadtree is more accurate than either level 0 or 1 because smaller blocks are represented. Each block 113, 1 14, 131, 132, and 141 which contain the foreground color, is partitioned into four sub-blocks to generate level 3. Higher levels are determined by recursive partiuoning of blocks which contain the foreground color until the smallest blocks contain a single pixel. A quadtree code is generated from a quadtree by ordering node values from the quadtree according to a predefined format. One format orders node values as read from left to πght and from the top down. For the quadtree of Fig. IB, a quadtree code is 1 1 1011 j 001111001000. (The symbol I is shown to separate quadtree code into levels for the reader's convenience and is not part of the quadtree code.) Quadtree codes often require less memory to store than do pixel maps and can be transmitted faster than a pixel map. One disadvantage of ,the described quadtree code is that each block is restπcted to a single color. A method that permits an efficient descnption of vanation m of data values over the area of each block would be desirable. SUMMARY OF THE INVENTION In accordance with an embodiment of the present invention, a method is provided for generating quadtree codes with embedded Walsh transform coefficients. The method uses a bottom- up recursive process for pruning a quadtree and typically starts by partiuoning a two dimensional data structure into a level N ur. -m partition which has 4 N blocks corresponding to the leaf nodes of a balanced quadtree. Each block in the level N partition comprises a matrix of pixel values. The matrices of pixel values are Walsh transformed, and a preselected subset of the Walsh transform coefficients are kept to approximate each block. The kept Walsh transform coefficients are referred to as a Walsh transform description. A level N- 1 uniform partition of the two dimensional data structure contains 4 N" ' disjoint blocks, each block being the union of four blocks from the level N partition. From the kept Walsh transform coefficients for the level N blocks, Walsh transform coefficients for blocks in the level N- 1 uniform partition are calculated. Also calculated is a measure of the distortion per block caused by replacing Walsh transform description of four blocks in the level N partition with a Walsh transform description of one block in level N-1 partition. When the measure of the distortion is less than a predefined threshold T m , nodes corresponding to the four level N blocks are pruned from the quadtree, so that a node corresponding to the union of the four blocks is made a leaf node. Only a preselected subset of the Walsh transform coefficients for the leaf nodes are kept. The pruning of the quadtree continues recursively through all the quadtree's levels. A quadtree code constructed from the pruned quadtree contains, in a predefined order, values for every node in the pruned quadtree, each value indicating whether a corresponding node is a leaf node. The kept Walsh transform coefficients are embedded into the quadtree code following corresponding leaf nodes. Often the Walsh transform coefficients are quantized using uniform step size and then variable length coded for transmission. In accordance with another embodiment of the invention, the values in a quadtree code follow a walking-the-tree order, wherein the node values follow an order defined by a succession of branches, each branch ending with a leaf node. In the quadtree code, after the value representing a leaf node, information such as Walsh transform coefficient is embedded to describe the data in the block corresponding to the leaf node. The walking-the-tree order permits the beginning of coding and transmission of a quadtree code to be before the entire quadtree is known and permits decoding of the quadtree code when the first branch is complete. Another embodiment of the present invention comprises a video/image coder which converts a pixel map representing a still image or difference image into a quadtree code with embedded Walsh transform coefficients. Still another embodiment in accordance with the present invention is a decoder which converts a quadtree code with embedded Walsh transform coefficients into a pixel map. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1A shows a two color image that can be represented by a pixel map. Fig. IB shows a level 2 quadtree representing the image of Fig. 1A. Fig. 1C shows blocks coπesponding to leaf nodes of level 1, level 2, and level 3 quadtrees representing the image of Fig. 1A Fig. 2 shows a partition coπesponding to leaf nodes of a balanced quadtree and partiuons which correspond to a quadtree after two levels of pruning. Fig. 3 shows level 1 and level 2 uniform paruuons of the image of Fig. 1A. Fig. 4 shows a walking-the-tree order for the nodes of a quadtree code corresponding to the image of Fig. 1A. Figs. 5 and 6 show the pnoπty of branches and blocks duπng a bottom-up tesung and pruning of a quadtree Fig. 7 shows a representation of a four color image which is pruned to determine a quadtree. Fig. 8 shows two by two, four by four, and eight by eight Walsh transformation matnces. Fig. 9 shows a factorization of an eight by eight Walsh transformauon matπx into three sparse matnces. Fig. 10 shows a level 3 balanced quadtree structure. Fig. 11 shows a block diagram of a video/image codec in accordance with an embodiment of the present invenuon. Fig. 12 shows an order for transmission of a four by four matrix of Walsh transform coefficients. Similar or identical items in different figures have the same reference numerals or characters. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Quadtrees can be constructed from the bottom up starting with a balanced quadtree structure that has leaf nodes corresponding a level N uniform paruuon which divides a two dimensional data structure into 4 N blocks of data. Nodes can be removed (or pruned) from the quadtree by tesung and mergmg sets of four blocks. In Fig. 2, a level 3 uniform partition divides a two color video image into sixty four (4 3 ) blocks of pixels. For simplicity, the blocks in Fig. 2 are all the same size. However, unequal blocks can be used, if blocks represented by a quadtree code can be identified. Generally, the choice of initial paruuon determines the accuracy of the quadtree representation of a two color image When each block holds only a single pixel the quadtree representauon provides an exact representauon of the image If more than one pixel is in the lniual blocks of the paruuon then the quadtree representauon is exact only for special images such as two color images where every block of the miual paruuon of the image contains only a single color Blocks 31 1-314 in the initial uniform partition can be tested to determine if blocks 311-314 should be merged to a single block 310 For a two color image, a test can determine if any of the blocks 31 1-314 contains the foreground color If any do, the blocks are not merged. If none do, the blocks are merged, and the four nodes which coπespond to the blocks are pruned from the quadtree For grey scale or mulucolor images, one type of test determines whether four adjacent blocks have the same color or intensity, and if the blocks all do, the blocks are merge to a larger block having a single uniform color or intensity Other tests for merging are disclosed below When four blocks are merged, they form a block which is part of a coarser uniform paruuon that corresponds to a lower level of the quadtree Accordingly, each level of the quadtree has a corresponding uniform paruuon from a seπes of uniform paruuons A rule or look-up table which identifies the blocks in the uniform paruuons is necessary for decoding a two dimensional data structure from a quadtree code For example, when a quadtree code mdicates that a block has a uniform color, the size and locauon of the block must be known before the quadtree code can be decoded One of the simplest seπes of uniform paruuons corresponding to the levels of a quadtree is formed by repeated equal quartering of the image. The level 3 uniform paruuon of Fig. 2 and level 1 and 2 uniform paruuons of Fig 3 illustrate a seπes of uniform paruuons formed by equal quartenng Using equal quartering, an image which is 512-by-512 pixels and has a level 0 uniform paruuon that is one 512-by-512 pixel block, a level 1 uniform partition that is four 256-by-256 pixel blocks, a level 2 uniform paruuon that is sixteen 128-by-128 pixel blocks, and so on to a level 9 uniform partition which is 262,144 blocks each containing a single pixel. In a bottom up construcuon of a quadtree, pruning the uiiual balanced quadtree creates a quadtree with leaf nodes corresponding to an intermediate paruuon. Blocks in the intermediate paruuon are then tested and merged if the blocks meet the appropnate conditions. In Fig. 2, blocks 351-354 contain only the background color and are merged to form block 350 which is one of the blocks in the level 1 uniform paruuon. Blocks 310 and 320 cannot be merged because neither block 330 nor block 340 is in the intermediate paruuon Generally mergers and pruning of the quadtree continue recursively through one or more intermediate partitions unul no further mergers are possible. At that point, the quadtree paruuon obtained contains only the blocks which coπespond to leaf nodes of the pruned quadtree. A quadtree code can be determined by providing a binary value for each node in the pruned quadtree, for example a zero for leaf nodes and a ones otherwise, then ordering the binary values in a predefined order. For example, as described above, all the values for level 0 of the pruned quadtree, then level 1 , then level 2, and so on to the highest level of the quadtree. In accordance with the present invention, another ordering of the values, referred to as walking-the-tree order, can be used. According to the walking-the-tree order, the quadtree code starts with a lowest level value, typically level 0 value, and proceeds down a branch until a leaf node is reached. The order then returns up the branch to the highest node which has one or more branches that have not been described, then follows the nodes down a not yet described branch until a next leaf node is reach. The order of values continues in this fashion branch by branch until all the values in the quadtree are given. Fig. 4 shows the quadtree of in Fig. IB and illustiates one example of a walking-the-tree order. The walking-the-tree order illustrated in Fig. 4 describes node values on each branch in order from lower level to higher level until a leaf node is reached. The branches are selected according to a predefined priority for each node. When a node has multiple branches which have not been described, the branch to a higher priority node is followed. The priority for the nodes is given by the location of the corresponding block as indicated in Fig. 5. The node corresponding to the top- left block has highest priority, the top-right block is second, the bottom-left block is third, and the bottom-right block has lowest priority. Once a leaf node is reached, the branch is traced back down to the highest level node which has a branch containing node values not given, then the highest priority branch having values not given is followed. Branch after branch is followed in this manner until all of the node values in the quadtree are given by the quadtree code. Using the above disclosed conventions, the first branch in Fig. 4 runs from node Nl to node N2 to leaf node N3. Node N2, the next highest node, has three branches with node values not given. The three branches from N2 contain only leaf nodes N4, N5, and N6 which are given in that order. After the last branch from N2 is completed, the next branch is from node Nl and contains only the leaf node N7. The following branch is also from node Nl and contains node N8 and N9, then the three branches from N8, each containing only node N10, Nil, or N12. The walking-the- tree order continues in the same manner until all the branches of the quadtree are described giving the quadtree code 11001101 1 10011000. With a walking-the-tree order, initial values of a quadtree code can be transmitted as soon as the first branch is known, and bottom-up determination of a quadtree can proceed branch by branch. Transmission of a quadtree code need not be delayed while the entire quadtree is determined. For example, in the level 2 uniform partition of Fig. 3, block 310 corresponds to node N3, block 360 corresponds to node N2, and the entire image coπesponds to node Nl. Testing blocks 341, 342, 343, and 344 (Fig. 2) indicates that blocks 341, 342, 343, and 344 cannot be merged. Therefore, blocks 310, 320, 330, and 340 can not be merged, and nodes Nl and N2 have value one. Since block 310 is uniformly the background color, N3 is zero, the first branch of the quadtree is known, and the branch NI-N2-N3 can be transmitted without determining any other nodes or any complete levels. Prior art quadtree codes describe a complete lower level before describing any values in the next higher level, so with a bottom-up determination of the quadtree, the entire quadtree must be determined before the initial values of the prior art quadtree code are provided. Accordingly, transmission of a quadtree code according to the prior art order must be delayed until the entire quadtree is determined. Fig. 6 shows the order in which blocks of a level 3 uniform partition should be tested to d..if.rmine node values on branches in the sequence defined by walking-the-tree order disclosed above. The order of Fig. 6 permits transmission of a quadtree code while determining the remainder of the quadtree. Many other walking-the-tree orders could be employed which would change the sequence of the branches quadtree code and the order in which blocks are tested. The quadtree code described above does not provide color or intensity information for multicolor or grayscale images. Ones and zeros from the quadtree code indicate only the quadtree structure. In accordance with the present invention, color or intensity information can be embedded into the quadtree code. Fig. 7 shows a level 3 unifoπn partition of a four color image where a number in each block indicates the color of the block. To generate a quadtree, a set of four blocks corresponding to level 3 nodes can be tested to, determine whether all four blocks have the same color. If the four blocks have the same color, the blocks are merged and the coπesponding nodes are pruned from the quadtree leaving the node coπesponding to the union of the four blocks as a level 2 leaf node. The merger of the blocks in the uniform partition forms an intermediate partition, also shown in Fig. 7, which represents the leaf nodes of a partly pruned quadtree. In the intermediate partition, blocks coσesponding to level 2 leaf nodes are tested for possible further merger and pruning. After the level 2 leaf nodes are pruned, the level 1 leaf nodes are tested, but for the example image shown in Fig 7 no merger of level 1 nodes is possible Instead of tesung in complete levels, the color image can also be pruned according to a walking-the-tree order as described above Either pruning method provides a quadtree paruuon represenung the leaf nodes of a quadtree representauon of the image A quadtree code for the color image can be formed by embedding in the code color mformauon following every leaf node For example, a convenuonal quadtree code for the quadtree paruuon of Fig 7 is 1 | 1011 1 01 1 110011010 where the branch convenuon shown in Fig 5 is used Color mformauon can be provided immediately after every zero value leaf node and following the highest level leaf nodes having node value one According to this convenuon, a quadtree code describing the image Fig 7 is 1 | 10(2)1 1 | 0(0)1(121 1)1(01 11)1(121 1)1(1122)0(1)0(3)1 (2123)1(2213)0(3)1(2333)0(3) where the parentheses and the symbols | are not part of the quadtree code but are added for the reader's convenience to separate color information and levels respecuvely This quadtree code requires 85 bits, 34 two-bit numbers for color lnformauon and 17 bits for quaduee structure An uncompressed pixel map would require 128 bits, two bits for each block Color or intensity mformauon can also be embedded mto the quadtree code at the end of each level for example l | 1011(2) 1011110011010(01333) | (1211011112111122212322132333) Other embedding convenuons are possible and are not limited to four color images but can be used with any mulucolored or grayscale image Embedding the color mformauon in the quadtree code has advantages over provid g a quadtree code separate from color mformauon, for example following the quadtree code with all color mformauon For quadtree codes that follow a walking-the-tree order such as disclosed above, embedded color mformauon the quadtree code after each leaf node allows immediate construcuon of a block of the image before the complete quadtree code is known. Instead of embedding a single number for each leaf node to indicate a color or grayscale intensity for the block corresponding to the node, several coefficients can be embedded mto the quadtree code to describe vaπauon of pixel values over the coιτespondιng block. For example, coefficients for a polynomial or other funcuon which describes the vanauon of color or intensity over the area of a block can be embedded to the quadtree code In one embodiment of the invention, one or more Walsh transform coefficients, as defined below, descnbe the color or intensity of a block For simplicity, the following embodiments deal with grayscale images which have a pixel map descπb g a two-dimensional gπd of pixels where the intensity of each pixel is described by a single number in the pixel map. Generalizing to other two dimensional data structures such as pixel maps which use three numbers to indicate color components will be apparent from the embodiments disclosed. A pixel map of a grayscale image has rows and columns of intensity values and can be manipulated as a matrix using well known linear algebra and matrix notauon. Similarly, when a pixel map is partiuoned into blocks, each block can be manipulated as a matrix. In accordance with the present invention, a quadtree is chosen with leaf nodes that coπespond to different size blocks, but the same predetermined number of Walsh transform coefficients describes each block regardless of the size of the block. The number of pixels in each block which coπesponds to a leaf node is restricted by the requirement that the predetermined number of Walsh transform coefficients provide a sufficiently accurate approximation pixel variation over the block. Discrete Walsh transformations can be performed using matrix multiplication and N-by-N transformation matnces as shown in Fig. 8 for N equal to 2, 4, and 8. In Fig. 8, the symbol "-" stands for -1. Every value in a Walsh transformation matrix is either 1 or -1. Accordingly multiplication by a Walsh transformation matrix is performed by addition (or subtraction) of components. No multiplication (other than multiplication by one) is required. Accordingly, Walsh transformations can be calculated quickly by digital systems. For any N by M matrix x where N and M equal 2' and 2 J respectively for any positive integers i and j, the Walsh transform X of the matrix x is defined to be N W-x- W where N W and M W are respectively N-by-N and M-by-M Walsh transformation matrices. The components of the Walsh transformed matrix X are referred to as Walsh transform coefficients. Since the matrix product of Walsh transformation matrices "W^W equals N -I where I is the identity matrix, x equals ( N W-X^W)/(N-M) N-by-N Walsh transformation matrices can be factored into sparse matrices N A„ ..., N A Z where Z = log 2 N. The factorization of the 8 by 8 Walsh transformation matrix into three sparse matrices 8 A 3 • 8 A 2 • 8 A, is shown in Fig. 9. It can be shown that for any 2N by 2N Walsh transformation matrix that I N A Z 0 I I N A, 0 I 2N W _AA Z+1 - I I - ... - I I . I 0 N A Z I I 0 N A, I It can also be shown that 2N A Z+I equals δ (>4)J + (-1 ) <Λ) δ (N+ , A)J for even i and equals δ iV , t , Λ)l + (-1)^' " " δ (N+Λ+V4) for odd i, where i and j are row and column indexes respectively and take values between 1 and 2N, and δ ab is a kronecker delta which is 1 if a equals b and 0 otherwise. The Walsh transfoπnauon matnces shown in Fig. 8 are refeπed to as being in sequency order meaning that each row (or column) starung from the top (or left) has one more change in sign than does the preceding row (or column). With sequency order, a Walsh transform of a uniform matrix, i.e. a matπx where all the components are equal, has one non-zero Walsh transform coefficient, the top left coefficient. For a nearly uniform matnx, only the Walsh transform coefficients near the top left of the transformed matπx are significant. Accordingly, a subset of Walsh transform coefficients are sufficient to provide a good approximauon of a uniform or nearly uniform matnx. A balanced quaduee that exactly descnbes an image can be constructed for any square image having height and width equal to 2' pixels for some posiuve integer I. Other size images can be constructed from a collecuon of such square images. Fig. 10 shows a balanced quadtree having 64 leaf nodes. If each leaf node coπesponds to a block containing a single pixel, the quaduee of Fig. 10 combined with intensity mformauon or a single Walsh transform coefficient exactly descnbes the image If each block the level 3 of Fig. 10 is a two-by-two matπx, four Walsh transform coefficients per leaf node are sufficient to guarantee an exact representauon of the image, because the Walsh transform of two-by-two block only has four coefficients. Similarly, if a level 3 paruuon has N, by N, pixels per blocks, N, 2 Walsh transform coefficient guarantee an exact representauon. In accordance with one embodiment of the present invenuon, an exact quaduee is pruned to generate leaf nodes coπesponding to blocks that are approximately uniform so that the top-left Walsh transform coefficients descπbe the block to a desired accuracy. As the quadtree is pruned any Walsh transform coefficients not needed to descnbe a block are dropped. Walsh transform coefficients are determined recursively. The recursive relauon of the Walsh transform coefficients can be expressed m matrix notauon as follows. If four N-by-N matnces x„ x 2 , x 3 , and x 4 can be merged mto a 2N-by-2N matπx x then χ = The Walsh transforms of matnces x,, x 2 , x 3 , x 4 , and x are matnces X„ X 2 , X 3 , X 4 , and X respecuvely. Only the top-left N, 2 Walsh transform coefficients are kept during pruning, so that the Walsh transformauon matnces X„ X 2 , X 3 , X 4 , and X are approximated by matnces X',, X' 2 , X' 3 , X' 4 , and X' which have the form I a 0 I x- - I I I o o I where a is a N, by N, matrix and 0 represents appropriately sized matrices with all components equal to zero. It can be shown that X ] Y Λ 2 I I x = % • I I * 2N A 2 . | x 3 Xι I where 2N A Z „, is the sparse matrix described above and 2N A Z+I T is the transpose of matrix 2N A Z+I . From the form of matrix 2N A Z+ ,, it can be shown that only the top-left coefficients of the matrices X„ X 2 , X 3 , and X 4 , i.e. only X'„ X' 2 , X' 3 , X' 4 , are required to determine X\ the top-left N, 2 of X. Accordingly, after each pruning of the quadtree (or merger of blocks), the Walsh uansform coefficients of new leaf node block can be calculated using only the kept Walsh transform coefficients. There is no need to calculate from the pixel level or to temporarily store more than the N, 2 Walsh transform coefficient values which are kept to describe the higher level blocks. Each time the quadtree is pruned, four blocks x,, x 2 , x 3 , and x 4 are merged into one block x, and if every block x : , x 2 , x 3 , x 4 , and x is described by the same number N, 2 of Walsh transform coefficients, the total number of coefficients describing the image is decreased by 3 times N, 2 . Typically, this increases distortion of a reconstructed image. One measure of the distortion is the square-error which provides a distortion per block. The square-error compares the original image with an image reconstructed from the quadtree code. From the top-left N, 2 Walsh transform coefficients kept in the quadtree code, a decoded image has four pixel matrices x'„ x' 2 , x' 3 , and x' 4 or, if the four are merged, one pixel matrix x\ The pixel matrices x',, x' 2 , x' 3 , x' 4 , and x' are inverse Walsh transformations of matrices X',, X' 2 , X' 3> X' 4 , and X' described above. The square-error distortion caused by describing the block x with N, Walsh transform coefficients is || x-x' || , the sum of the squares of all components of the matrix x-x'. It can be shown using standard linear algebra techniques that || x-x' ll equals || x,-x', || + || x 2 -x' 2 || + || X j -x',11 + II x 4 -x' + trBB T /(2N 2 , where for Z = log, N I X' B = 2N A ZtI - I Z+1 T - X'. The square-error resulting from using the block x as a leaf node is the sum of the square-error caused of blocks x',, x' 2 , x' 3 , and x' 4 plus an additional error caused by merging. Because matrix B is completely determined by the Walsh transform coefficients X',, X' 2 , X' 3 , and X' 4 , the additional square-eπor can be determined recursively from the saved Walsh transform coefficients, and there is no need to return to a pixel level calculation or to save extra Walsh uansform coefficient values for calculation of the additional square-eπor. Another measure of the additional distortion is the sum of the absolute values of die matrix B which is requires fewer multiplications to calculate because the components of B do not need to be squared. Still another measure of the additional distortion is the maximum of the absolute values of coefficients in die matrix B. Determining which measure is the best for images is subjective because for images the goal is to have decoded images which are the least changed from the original according to a human view. Both the sum and the maximum absolute value of the coefficients in B have been experimentally found to provide a decoded image which appears close to the original. Pruning of a quadtree can be done recursively by merging only the sets of four blocks which cause the smallest additional error. A pruning threshold T„ can be set such that if the additional error caused by pruning is less than the pruning threshold then nodes are pruned. The value of the pruning threshold T m and the type of measure for the error determine the accuracy of the quaduee description. For the square-error, the additional eπor is the trace of BB T /(2N) 2 . For absolute sum error, the additional error is the sum of the absolute values of the coefficients of B divided by (2N 2 . For absolute maximum eπor, the additional eπor is the maximum absolute value of the coefficients of B and can be determined without division. Typically, Walsh transform coefficients are determined to more significant bits than are embedded in a quadtree code, and the Walsh transform coefficients are quantized to a desired number of possible values. The quantization causes distortion because the quantized values only approximate the correct coefficient values. As is well known in the art, for a fixed bit rate transmission, the optimal quantization technique for minimizing distortion caused by quantization depends on the distribution of values to be quantized and on the method of coding quantized values. For a generalized gaussian distribution and variable length coding of the Walsh transform coefficients, quantization with uniform step size minimizes the distortion for a fixed bit rate transfer. Uniform step size divides the, Walsh transform coefficients by a fixed quantization step sizes q, and then rounds the result to the nearest integer. A different step size q can be chosen for each coefficient so that the largest anticipated Walsh transform coefficient falls within the desired range of values. As disclosed below, for a particular embodiment of the invention, the same quantization step size can be used for all coefficients in a block. Different step sizes q._j can be used for different size blocks. Typically, Walsh transform coefficient magnitudes are proportional to N 2 where N-by-N is the block size. Step sizes q N equal to q 0 -N : compensate for the increased in coefficient size for larger blocks. Quantizauon can be improved by taking into account that eπor caused by quantization of the coefficients of a large block disturbs more pixels than quantization for a small block. An estimate of the variance of the quantization error, assuming uniform distribution, is proportional to N 2 -q 2 . Accordingly, a better quantization method uses step size q N equal to q 0 -N for blocks of size N. A further restriction of the step size is that the resultant quantization distortion should maintain the image accuracy of the pruning threshold T m . Accordingly, the number of possible values after quantization should be minimized to reduce the number of bits required to express the quantized values, but enough possible values should be provided so that the distortion caused by quantization does not outweigh the distortion caused by pruning. Tables 1 and 2 show values for the pruning threshold T m and quantization constant q which provide compatible amounts of distortion. T m is a limit for the square-eπor (trBB T /(2N) 2 ) divided by four, and the step size of the quantized coefficients is 2N*q. TABLE 1 TABLE 2 After the coefficients are quantized, they are variable length coded. Variable length coding such as Huffman coding requires fewer bits for the most frequent values and more bits for the least frequent values so that the average size of the quadtree code is reduced by variable length coding. A decoder which receives the quadtree code typically uses a look-up table to decode the Huffman coding and then muluphes quanuzed Walsh transform coefficients by the step size q N to restore approximate Walsh transform coefficients The decoder determines the block size and the appropπate step size q N from the quadtree structure Fig 1 1 shows a block diagram including a video/image codec in accordance with an embodiment of the venuon The video/image codec may be used, for example, m apphcauons such as a video telephone communicauons or an image archive system for stoπng compressed images As shown in Fig. 11, the coder side of the codec connects to a camera 1105 or some other source which provides video signals that represent a seπes of images or frames which create the appearance of a moving image Any known or yet to be developed video format for video signals may be used, and can be converted from one format to another by a converter 1110 if desired Most current video signal formats provide each frame as a seπes of hoπzontal lines which can be captured in a camera buffer 1115 to created a two dimensional data structure such as a pixel map for a frame A frame memory 1 120 receives a pixel map for the frame from camera buffer 1 115. Typically, two consecuuve frames in a moving image are closely related to each other By compaπng two consecuuve frames, the amount of mformauon in the second frame can be reduced by subtracting the. mformauon already fransmitted with a previous frame Many techniques are known for reducing the amount of mformauon per frame of a seπes of frames In the embodiment of Fig. 11, a mouon estimator 1125 compares the frame in frame memory 1120 image to previous frame stored a frame buffer 1130 and determines an average offset of mformauon between frames and generates mouon vector which are transmitted to a decoder. A shifted previous frame is then subtracted 1135 from the frame in frame memory 1120 to provide a difference image. Mouon estimator 1125 and subtracuon 1135 are not necessary for still images such as found in an image archive system. Accordingly, a still image codec can be made by eliminating motion estimator 1125 and subtracuon 1135, so that a still image instead of on a difference frame is coded A quadtree Walsh transform (QTWT) processor 1140 creates a quadtree code and quanuzes the Walsh transform coefficients for the difference frame using the methods disclosed above. Such processors may be implemented in hardware or in software (as in the Appendix.) In one embodiment, processor 1140 breaks the difference frame the a seπes of square sub-images such as seπes of 16 by 16 pixel sub-images and provides a quadtree code for each separate sub-image Processor 1140 also quanuzes the Walsh transform coefficients. It has been experimentally determined that difference frames for a wide vanety of moving images have Walsh transform coefficients that with the excepuon of the top-left (or DC) coefficient have values that approximately follow a Lapacian distπbuuon where the probability of a coefficient having a value x is approximately proportional to exp{- 1 x | }. In the embodiment where a frame is divided mto sub- images, the difference between the DC coefficient for neighboπng sub-images is also approximately Lapacian A bit rate distortion funcuon can be used to determine bit rates and step sizes for every Walsh transform coefficient in an N-by-N block Experiments show that step size assignment which minimize the quanuzauon distortion subject to the constraint of a constant bit rate are almost the same for every kept coefficient in an N-by-N block, even though the absolute magnitudes of coefficients vary The quadtree codes are combined with the previous frame in buffer 1130 for internal use and transmitted through a source encoder 1145, a channel encoder 1 150, and a channel buffer 1 155 to a channel Decoding die quaduee code and combimng the decoded difference image to the previous frame in buffer 1130 provides a decoded frame which the same as the frame generated by a decoder Source encoder 1145 vaπable length codes the Walsh transform coefficients in quadtree code In accordance with one embodiment of the present invenuon, after quanuzauon according to block size, the Walsh transform coefficients for a difference image range from -255 to 255, (511 possible values) with the most likely value be g 0. To create Huffman codes for this embodiments, the possible values can be divided into eight classes C 0 -C 8 as shown in Table 3 CLASS Co C, c 2 C 3 C -4 4 (24) c 5 c, The Huffman codes used for each class depends on the number of Walsh uansform coefficient which describe each block. The Huffman codes for classes C 0 -C 8 shown in Tables 4, 5, and 6 are for one, four, and sixteen Walsh transform coefficients per block respectively. (25) TABLE 5 CLASS CODE (26) C : 010 C, 0111 C. 001110 0011110101 (27) 001111010011011 c, 001111010011010 c 8 001111010001111 R(2) 00110 R(3) 01100 R(4) 01101 R(5) 0011111 R(6) 00111100 R(7) 001111011 R(8) 001111010000 R(9) 0011110100010 R(10) 001111010010 R(ll) 0011110100111 R(12) 00111101001100 R(13) 001111010001110 R(14) 001111010001101 R(15) 001111010001100 EOB 000 In Tables 4, 5, and 6, the Huffman code for any value within a class is represented by the class code combined with a sign bit and a fixed length select value when necessary. In Tables 5 and 6, EOB (end of block) indicates all the remaining Walsh transform coefficients for a block are zero. In Table 6, R(2) to R(15) indicate two to fifteen consecutive zeros respectively. Fig. 12 shows a zigzag order for a four-by-four block of Walsh transform coefficients. With the pruning techniques described above and the order shown in Fig. 12, the last coefficients have the highest probability of being zero. Channel encoder 1150 adds error checking codes. Channel buffer 1155 temporarily stores portions of the quadtree code so the rate of transmission does not exceed the capabilities of an output channel carrying the quadtree code. Fig 1 1 also shows a decoder portion which decodes quaduee codes which are received on an input channel Channel buffer 1 160 stores input quaduee codes so that data is not lost when the transmission rate on the input channel temporarily exceeds the processing rate of the decoder A channel decoder 1 165 removes the uansmission eπor encoding and checks for uansmission eπors A source decoder 1 170 decodes the Huffman coding of Walsh uansform coefficients in the quaduee code and provides the decoded values to a QTWT decoder 1 175 QTWT decoder 1175 identifies the blocks coπesponding to the leaf nodes of the quadtree code, and performs an inverse Walsh ansiormauon on the Walsh transform coefficients coπesponding to the leaf nodes The idenufied blocks are then filled with the values provided by the inverse Walsh uansformauons to form a difference image Adder 1185 combines the difference image with a shifted pixel map according to a received mouon vector of a previous frame stored in frame buffer 1180 to generate a pixel map for a new frame The new frame is then stored in frame buffer 1180 for use with the next difference image The pixel map for the new frame also passes through a filter 1190 which can, for example, smooth discontinui es in the new frame After filtering, the new frame is then displayed on display 1195 Alternauvely, the new frame can be displayed without filtenng The appendix contains lisungs of C language subrouunes which encode and decode quadtree codes with embedded Walsh transform coefficients. For encoding, subroutine qtwt_quan_enco2D.c is the top level subrouune which calls the subrouunes necessary for creating a quaduee code, quantizing, and vaπable length coding. Subrouune qtwt_grow_costt.c generates a balance quadtree. Subrouune qtwt_prune_costtc prunes the quadtree. Subrouune output_bιts.c forms and outputs the quadtree code For decoding, subrouune qtwt_quan_deco2D.c is the top level subrouune which calls the subrouunes necessary for vaπable length decoding and reconstrucuon of a frame. Subrouune mput_bιts2D.c decodes a block from the Walsh code. Subrouunes bιts_to_matnx2D.c, ιnput_bιts2D.c, and ιnρut_bιts.c vaπable length decode an input quadtree code. The other subrouunes are general purpose and can be used both during coding and decoding. Subrouune one_d_wt.c one_d_ιwtc performs a recursive one dimensional Walsh fransfoπnauon and mverse Walsh transformauon. Subroutine one_d_wt_rc.c performs a single step one dimensional Walsh transform. Subrouune two_d_ιw.c and two_d_ιwt.c perform a two dimensional (or matπx) Walsh transformauon and inverse Walsh uansform respecuvely Although the present invenuon has been descnbed with reference to particular embodiments, the descπpuon is only an example of the invention's application and should not be taken as a limitation. In particular, even though much of preceding discussion was aimed at processing of video images and in particular pixel maps, present invenuon can be more generally applied to description of any array of two dimensional data structure. APPENDIX /* bits_to_matrix2D.c: subroutine to input bits and to decode them into blocks; for Nt = 2; Copyright by Xiaonong Ran */ #include "input_bits2D.c" void bits_to_matrix2D( temp_2d, init_v, fla l, fρ_in, code, length, step_size, nn4, trunc, buffer_input, bits_to_input, treeb ) float **temp_2d, **init_v, nn4; int *flagl; short *code, *length; FILE *fp_in; float step_size; /* quantization step size. */ int *buffer_input, *bits_to_inρut; struct entry *treeh; { int k6, i6, j6, itemp, runj, il; /* zigzag scaning */ k6 = 0; i6 = 0; j6 = 0; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, treeh, bits_to_input, buffer_input, code, length, &itemp, &run_l ); if( runj > 0 ){ temp_2d[i6]fj6] = 0.0; run_I~; if( π nj = 0 && k6 < trunc*trunc-l ) input_bits2D( fp_in, ueeb, bits_to_input, buffer_input, code, length, &itemρ, &run_l ); } else{ temp_2d[i6][j6] = itemp*step_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, treeh, bits_to_input, buffer_input, code, length, &i_emp, &run_l ); } while( i6 != uτιnc-1 II jό != uτιnc-1 ){ if( i6 = 0 ){ j6++; k6++; if( runj > 0 ){ temp_2d[i6][j6] = 0.0; runj-; if( run_l = 0 && k6 < ιrunc*trunc-l ) input_bits2D( fp_in. treeh, bits_to_input, buffer_input code, length, &itemp, &run_l ); ) else( temp_2d[i6][j6] = itemp*step_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, ueeh, bits_to_input, buffer_input, code, length, &itemp, &run_l ); } for( il = j6-l; il > -1 ; il-- )( j6~; i6++; k6++; if( run_l > 0 ){ temp_2d[i6][j6] = 0.0; runj-; if( run_l = 0 && k6 < trunc*trunc-l ) inρut_bits2D( fp n, treeh, bits_toJnput, buffer nput, code, length, &itemp, &runj ); } else. temp_2d[i6](j6] = itemp*step_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fpjn, U"eeh, bits_toJnput, buffer_input, code, length, &itemp, &runj ); } } } else if( j6 = 0 && i6 < trunc-1 ){ i6++; k6++; if( runj > 0 ){ temp_2d[i6][j6] = 0.0; runj-; if( runj = 0 && k6 < trunc*trunc-l ) input_bits2D( fpjn, treeh, bits_to jnput, buffer nput, code, length, &itemp, &runj ); ) else{ temp_2d[i6] j6] = itemρ*steρ_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, treeh, bits_tojnput, bufferjnput, code, length, &itemp, &runj ); ) for( il = i6-l; il > -1; il-- ){ i6-; J6++; k6++; if( run_l > 0 ){ temp_2d[i6] j6] = 0.0; runj-; if( run_l = 0 && k6 < trunc*trunc- 1 ) input_bits2D( fp_in, Ueeh, bits_to_input, bufferjnput code, length, &itemp, &runj ); ) else} temp_2d[i6][j6] = itemp*step_size*nn4; if( k6 < trunc*trunc- 1 ) input_bits2D( fp_in, treeh, bits_to_input, buffer_input, code, length, &itemp, &runj ); } } } else if( i6 = trunc-1 ){ j6++; k6++; if( runj > 0 ){ temp_2d[i6][j6. = 0.0; runj-; if( run_l — 0 && k6 < trunc*trunc-l ) input_bits2D( fp_in, treeh, bits_toJnput, buffer nput, code, length, &itemp, &runj ); } else{ temp_2d[i6][j6] = itemp*step_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, ueeh, bits_toJnput, buffer_input, code, length, &itemp, &mnj ); } for( il = j6+l; il < trunc; il++ ){ i6-; J6++; k6++; if( runj > 0 ){ temρ_2d[i6][j6] = 0.0; runj--; if( runj = 0 && k6 < trunc*trunc-l ) inρut_bits2D( fp_in, treeh, bits_to_input, bufferjnput, code, length, &itemp, &runj ); } else{ temρ_2d[i6]|j6] = itemp*steρ_size*nn4; if( k6 < trunc*trunc-l ) inρut_bits2D( fp_in, freeh, bits_toJnput, buffer_inρut, code, length, &itemρ, &run_l ); else if( j6 == trunc- 1 ){ i6++; k6++; if( run_l > 0 )( temp_.2d[i6][j6] = 0.0; runj-; if( run_l = 0 && k6 < trunc*trunc-l ) input_bits2D( fpjn, treeh, bits_to_input, buffer_input, code, length, &itemp, &runj ); ) else{ temp_2d[i6]|j6] = itemp*step_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp_in, treeh, bits_to_input, bufferjnput, code, length, &itemp, &runj ); } for( il = i6+l; il < trunc; il-H- ){ i6++; j6~; k6++; if( runj > 0 ){ temp_2d[i6]_j6] = 0.0; run -; if( runj = 0 && k6 < trunc*trunc-l ) input_bits2D( fpjn, treeh, bits„to_input, buffer_input, code, length, &itemp, &run J ); ) else{ temp_2d[i6]_j6] = itemp*steρ_size*nn4; if( k6 < trunc*trunc-l ) input_bits2D( fp n, treeh, bits_to_inρut, bufferjnput, code, length, &itemp, &run ); /* end of zigzag scaning */ } /*input_bits.c: subroutine to input bits and to variable length decode them into indices. Copyright by Xiaonong Ran */ void input_bits( fpjn, huffuee, bits_to_input, bufferjnput, code, length, index_out ) FILE *fp_in; struct entry *huftuee; int *bιts_to_mρut, *buffer_mρut, *code, *length, *mdex_out; { struct entry *tree_poιnter; uee_poιnter = huffuee; whιle( free_pomter->flag_node == 0 ) { ιf( *biLs_to_ιnput == 0 ){ /* Read the next byte if*/ *buffer_mput = getc( fp_ιn ), /* bits are left in buffer*/ *bιts_to_ιnput = 8; } ιf( *buffer_ιnρut & 1 ) tree_pomter = tree_poιnter->leaf 1 ; else tree_pomter = tree_poιnter->leafO; *buffer_mput »= 1; *bιts ojnput -= 1 ; *mdex_out = uee_poιnter->mdex; /*mput_bιts2D.c: subrouune to input bits and to decode them mto quantized values, run-lengths and EOBs; for Nt=2. #mclude "mput_bιts.c" Copyπght by Xiaonong Ran */ void ιnput_bιts2D( fp_m, huffuee, bits ojnput, bufferjnput, code, length, index, runjen ) struct entry *hufftree; mt *bιts_tojnput, *bufferjnput, *code, *length, *mdex, *runjen; { int itemp, ιndex_out, sign , i2; input _bιts( fpjn, hufftree, bitsjojnput, bufferjnput, code, length, &mdex_out ); *runjen = 0; if( mdex_out == 0 ) { *run Jen = 4; /* for EOB */ } else ιf( ιndex_out == 1 ) { itemp = mdex_out-l; *ιndex = itemp; } else if( index_out < 7 ){ itemp = index )ut- 1 ; if( *bits o_input == 0 ){ *buffer_input = getc( fp_in ); * bitsjojnput = 8; } if( *buffer jnput & 1 ) sign = 1 ; else sign = -1; *buffer jnput »= 1 ; *bits_to Jnput -= 1 ; itemp *= (-l)*signj; *index = itemp; } else if( index πit < 10 ){ itemp = index .ut-4; if( *bitsjo_inpuι == 0 ){ *buffer_input = getc( fp ^i ); *bits_to Jnput = 8; } if( *buffer jnput & 1 ) signj = 1 ; else signj = -1 ; *buffer jnput »= 1 ; *bits_to Jnput -= 1 ; for( i2 = 0; i2 < 1; i2++ ){ if( *bits o_input == 0 ){ *buffer_input = getc( fρ_in ); ♦ bitsjojnput = 8; } itemp «= 1; if( *buffer Jnput & 1 ) itemp += 1; *buffer jnput »= 1 ; *bits_to Jnput -= 1; ) itemp *= (-l)*signj; *index = itemp; } else if( index_out < 15 ){ itemp = index_out-7; if( *bits o_input == 0 ){ *buffer_input = getc( fp_in ); *bits_to nput = 8; } if( *buffer jnput & 1 ) signj = 1 ; else signj = -1; *buffer Jnput »= 1; *bits o Jnput -= 1 ; for( i2 = 0: i2 < 2; i2++ ){ if( *bits o jnput == 0 ){ ♦ bufferjnput = getc( fpjn ); *bits_to nput = 8; itemp «= 1; if( *buffer_input & 1 ) itemp += 1 ; *buffer_input »= 1 ; *bits_t Jnput -= 1 ; itemp *= (-l )*signj; ♦ index = itemp; else{ itemp = 1 ; if( *bits o jnput == 0 ){ ♦ bufferjnput = getc( fp_in ); ♦ bits_toJnput = 8; if( *buffer_input & 1 ) signj = 1 ; else signj = -1 ; ♦ bufferjnput »= 1 ; ♦ bitsjojnput -= 1 ; for( i2 = 0; i2 < index_out-10; i2++ ){ if( ♦ bitsjojnput == 0 ){ ♦ bufferjnput = getc( fp_in ); ♦ bitsjojnput = 8; } itemp «= 1; if( ♦ bufferjnput & 1 ) itemp += 1 ; ♦ bufferjnput »= 1 ; ♦ bits o Jnput -= 1; } itemp *= (-l)*signj; ♦ index = itemp; /*one_dJwt.c: subroutine to perform complete fast recursive 1-D inverse Walsh Transform. Copyright by Xiaonong Ran ♦ / void one_d_iwt_2( transjn, truncj, data_out, flag ) float ♦ transjn; /* transjn: 1-D trans, coeff. array in.*/ int truncj; /* traunc : size of transform coefficients computed.*/ float *data_out; /* data_ u_ 1-D data array out.*/ int flag; /* flag=l: the last recursive stage with the factor 1/2*/ { float temp [2]; if( truncj >= 2 ){ temp[0] = uansjn[0] + transjn . l]; temp[ l ] = uansjn[0] - transjn[l]; da _out[0] = temp[0]; data_out . l] = tempflj; 1 else if( truncj == 1 ) { data_out[0] = transjn [0]; da_a_out. l] = trans_in[0]; } else { dam_out(0] = 0.0; data_out[ l] = 0.0; return; if( flag == 1 ){ data_out[0] /= 2.0; data_outt l] /= 2.0; void one_d_iwt_4( trans_in, truncj, data_out, flag ) float *trans_in; /* trans_in: 1-D trans, coeff. array in.*/ int truncj; /* tiauncj: size of transform coefficients to be computed.*/ float *data_out; /* data_out; 1-D data array out*/ int flag; /* flag=l : the last recursive stage with the factor 1/2*/ float temp[4]; if( truncj >= 4 ){ one_d_iwt_2( transjn, 2, transjn, 0 ); one_d_iwt_2( trans_in+2, 2, transjn+2, 0 ); temptO] = trans jn[0] + uans_in[2]; tempfl] = trans jn[0] - trans_in[2]; temp[2] = transjnfl] - transjn[3]; temp[3] = trans ntl] + trans_in[3]; } else if( tnιncj == 3 ,){ one_dJwt_2( u-aιis_in, 2, transjn, 0 ); one_d_iwt_2( trans_in+2, 1, trans_in+2, 0 ); temp[0] - trans jn[0] + trans_in[2]; temptl] = fransJnfO] - trans_in[2]; temp[2] = transjn[l] - transjn[3]; temp[3] = transjnfl] + trans_in[3]; } else if( truncj == 2 ) { one_d Jwt_2( transjn, 2, transjn, 0 ); temp[0] = uansjn[0] tempfl] = transjn [0] temp[2] = uansjn[l] temp[3] = trans n[l] else if( truncj == 1 ) { one_djw__2( trans_in, 1, transjn, 0 ); temp[0] = Uansjn[0] te pfl] = transjn [0] temp[2] = uansjnfl] temp[3] = uansjn[l] } else { data_out[0_ = 0.0 data_out[l] = 0.0 data_out[2] = 0.0 data_out[3] = 0.0 return; if( flag == 1 ){ data_out[0_ = temp[0]/4.0: data_out[l] = temp[l]/4.0: data_out[2] = temρ[2]/4.0: data_out[3] = temp[3]/4.0: else { data_out[0_ = tempfO]; data_out[l] = temp[l]; data_out[2] = temp[2]; data_out[3] = temp[3]; } void one_d jwt_8( trans_in, truncj, data_out, flag ) float ♦ transjn; / ♦ transjn: 1-D trans, coeff. aπay in. + / int truncj; /* trauncj: size of transform coefficients to be computed.*/ float ♦ data .ut; / ♦ data_ou_ 1-D data array ouL^/ int flag; / ♦ flag=l: the last recursive stage with the factor 1/2*/ { float temp[8]; int i, j, sign; if( trunc_l == 0 ) { for( i = 0; i < 8; i++ ) data_out[i] = 0.0; return: } i = truncj - 4; ιf( ι >= 0 ) j = 4, else { j = truncj, ι = 0. one_d_ιw__4( uans_ιn, j, transjn, 0 ); one_djwt_4( (uansjn+4), I, (transjn+4), 0 ), ιf( l == 0 ) for( i = 0; ι < 8; ι++ ){ j = ι 2; temp[ι] = uansjn )]; } else for( l = 0; ι < 8; ι++ ){ j - ι/2; ιf( (((ιnt)((ι+l)/2)) & 1) > 0 ) sign = -1 , temp[ι] = transjnfj] + sιgn + tfans_ιn[j+4]; } ιf( flag == 1 ) for( l = 0; l < 8; ι++ ) data_out[ι] = temp[ι]/8.0; else for( l = 0; l < 8; ι++ ) data_out[i] = tempfi]; void one_d_ιwt_16( tfansjn, truncj, data_out, flag ) float *uans_m; /* tfans_ιn: 1-D trans, coeff. array m.*/ t trunc_l; / ♦ trauncj: size of transform coefficients to be computed.*/ float *data_out; / ♦ data_out: 1-D data array out.*/ int flag; /* flag=l: the last recursive stage with the factor 1/2*/ { float temp[16]; t l, j, sign; ιf( truncj = 0 ) { for( l = 0; ι < 16; 1++ ) data_out[ι] = 0.0; return; } i = truncj - 8; ιf( , >= 0 ) j = 8; else { j = truncj ' ; I = 0; one_djwt_8( trans_ιn, j, transjn, 0 ); one_d_ιwt _8( (trans jn+8), l, (transjn+8), 0 ); if( i == 0 ) for( i = 0; i < 16; .++ ){ j = i/2; te pfi] = Uansjnlj]; ) else for( i = 0; i < 16; i++ ){ j = i 2; if( (((int)((i+l)/2)) & 1 ) > 0 ) sign = -1 ; else sign = 1; temp[i] = trans_in[j] + sign*uansjn_j+8]; if( flag == 1 ) for( i = 0; i < 16; i++ ) data_out[i] = temp[i]/16.0; else for( i = 0; i < 16; i++ ) data__out[i] = temp[i]; void one_djwt_32( transjn, truncj, da_a_out, flag ) float *trans jn; /* transjn: 1-D trans, coeff. aπay in.*/ int truncj; /* tfauncj: size of uansform coefficients to be computed.*/ float *data_out; /* data_out: 1-D data array ouL*/ int flag; /* flag= 1 : the last recursive stage with the factor 1/2*/ float temp[32]; int i, j, sign; if( truncj = 0 ) { for( i = 0; i < 32; i++ ) data_out[i] = 0.0; return; i = truncj - 16; if( i >= 0 ) j = 16; else { j = truncj; i = 0; one_djwt_16( transjn, j, transjn, 0 ); one_djwt_16( (transjn+16), i, (transjn+16), 0 ); if( i == 0 ) for( i = 0; i < 32; _++ ){ j = i/2; tempfij " = trans jn[j]; ) else for( i = 0; i < 32; i++ ){ j = i 2; if( (((int)((i+l)/2)) & 1 ) > 0 ) sign = -1 ; else sign = 1 ; temp.i] = uans_in[j] + sign*uansjn[j+16]; if( flag == 1 ) for( i = 0; i < 32; 1++ ) data_out[i] = temp[i]/32.0; else for( i = 0; i < 32; i++ ) data_out[i] = temp[i]; void one_d_iwt_64( uans jn, truncj, data_out, flag ) float *uans jn; /* trans_in: 1-D trans, coeff. array in.*/ int truncj; /* tfauncj: size of transform coefficients to be computed.*/ float *da i_out; /* data_out: 1-D data array out*/ int flag; /* flag= l : the last recursive stage with the factor 1/2*/ float temp [64]; int i, j, sign; if( truncj = 0 ) { for( i = 0; i < 64; i++ ) data_out[i] = 0.0; return; } i = truncj - 32; if( i >= 0 ) j = 32; else { j - truncj; i = 0; one_d_iwt_32( transjn, j, tiansjn, 0 ); one_d_iwt_32( (trans jn+32), i, (trans jn+32), 0 ); if( i == 0 ) for( i = 0; i < 64; _++ ){ j = i 2; tempfi] = trans jn[j]; } else for( i = 0; i < 64; i++ ){ j = i/2; if( (((int)((i+l)/2)) & 1) > 0 ) sign = -1; else sign = 1 ; tempfi] = trans jn[j] + sign*ffansjn[j+32]; if( flag == 1 ) for( i = 0; i < 64; i++ ) data_out[i] = temp[i]/64.0; else for( i = 0; i < 64; ι++ ) data .ut_i] = temρ[i] void one_d_iwt( transjn, size, truncj, data_out ) float *uansjn; /* uansjn: 1-D trans, coeff. array in.*/ int size; /* size: size of the 1-D trans, coeff. array. ♦ / int truncj; /* trauncj: size of transform coefficients to be computed.*/ float *data_out; /* data_out: 1-D data array out*/ ( switch (size) f case 2: one_d jwt_2( uans_in, truncj, data_out, 1 ); break; case 4: one_d_iwt_4( uansjn, truncj, data_out, 1 ); break; case 8: one_d_iwt_8( tiansjn, truncj, data_out, 1 ); break; case 16: one_djwt_16( transjn, truncj, data_out 1 ); break; case 32: one_d jwt_32( transjn, truncj, data_out, 1 ); break; case 64: one_d_iwt_64( uansjn, truncj, data_out 1 ); break; default: printfC'Walsh Transform uses size 2, 4, 8, 16, 32 or 64 here\n"); break; /*one_d_wt.c: subroutine to perform complete fast recursive 1-D Walsh Transform. Copyright by Xiaonong Ran */ void one_d_wt_2( data jn, truncj, tians_out ) float *datajn; /* datajn: 1-D data array in.*/ int truncj; / ♦ uauncj: size of transform coefficients to be computed.^/ float ♦ trans_out; / ♦ trans )ut: 1-D uansform coefficient array out.*/ { float temp[2]; if( truncj >= 2 ){ tempfO] = datajnfO] + datajnfl]; temp[l ] = datajn . O] - datajn[l]; trans_out[0] = temp[0]; uans_out[l] = temp[l]; } else if( trunc_l == 1 ){ trans_out[0] = datajnfO] + datajnf l]; void one_d_wt_4( data jn, trunc_l, trans_out ) float *datajn; /* data_in: 1-D data array in.*/ int truncj; /* tiauncj: size of transform coefficients to be computed.*/ float *uans_out; / ♦ uans_out: 1-D transform coefficient array out*/ { float temp[4]; int truncjO; trunc JO = (truncj-l) / 2 + 1; one_d_wt_2( data jn, trunc JO, datajn ); one_d_wt_2( data jn+2, truncjO, data jn+2 ); if( truncj >= 4 ){ tempfO] = data_in[0] + data_in[2]; tempfl] = data_in[0] - datajn[2]; temρ[2] = data_in[l] - datajn[3]; temρ[3] = data_in[l] + datajn[3]; trans_out[0] = tempfO] ; trans_out[l] = temp[l]; trans_out[2] = temp[2]; trans_out[3] = temp[3]; } else if( truncj == 3 ){ tempfO] = datajnfO] + datajnf2]; tempfl] = datajnfO] - datajn[2]; temp[2] = datajnfl] - datajn[3]; trans_out[0] = tempfO]; trans Hitfl] = tempfl]; trans_out[2] = temp[2]; 1 else if( trunc_l == 2 ){ tempfO] = data_in[0] + data_in[2]; tempfl] = datajnfO] - datajn[2]; trans_out[0] = tempfO]; trans_outfl] = tempfl]; } else if( frunc_l == 1 ){ tempfO] = datajnfO] + datajn[2]; uans_out[0] = tempfO], void one_d_wt_8( datajn, trunc_l, uans_out ) float *data_ιn, /* data_m: 1-D data array in.*/ t truncj, /* tfauncj: size of uansform coefficients to be computed.*/ float *trans_out, /* trans_ ut: 1 -D transform coefficient array out.*/ { float tempfδ]; int truncjO, l, j, sign; truncjO = (truncj- 1) / 2 + 1 ; one_d_wt_4( datajn, truncjO, datajn ); one_d_wt_4( (datajn+4), truncjO, (datajn+4) ); ιf( truncj " > 8 ) truncj " = 8; for( i = 0, l < truncj; 1++ ){ j = L 2; ιf( (((ιnt)((ι+l)/2)) & 1) > 0 ) sign = -1; tempfi] = datajnfl] + sιgn*datajn[j-ι-4]; } for( ι = 0; l < truncj; ι++ ) trans_out[ι] = tempfi]; } void one_d_wt_16( datajn, truncj, uans_out ) float *datajn; /* datajn: 1-D data array va.*l int truncj; /* uaunc j: size of transform coefficients to be computed.*/ float *trans_out; /* uans_out: 1 -D transform coefficient array out*/ { float tempfl 6]; mt truncjO, I, j, sign; truncjO = (trunc J-l) / 2 + 1; one_d_wt_8( datajn, truncjO, data_ιn ); one_d_wt_8( (datajn+8), trunc JO, (datajn+8) ); ιf( truncj > 16 ) truncj = 16; for( l = 0; i < truncj; ι++ ){ j = ι/2; ιf( (((ιnt)((ι+l)/2)) & 1) > 0 ) sign = -1; tempfi] = datajnfj] + sιen*datajnfj+8], } for( l = 0; l < truncj; _++ ) trans_outfi] = tempfi]; void one_d_wt_32( datajn, truncj, uans_out ) float *da_ιjn; /* datajn: 1-D data array in.*/ int truncj; /* tiauncj: size of uansform coefficients to be computed.*/ float *uans_out; /* tians_out: 1-D transform coefficient array out.*/ ! float temp[32]; int truncjO, i, j, sign; truncjO = (truncj- 1) / 2 + 1 ; one_d_wt_16( datajn, truncjO, datajn ); one_d_wt_16( (datajn+16), truncjO, (datajn+16) ); if( trunc_l > 32 ) truncj = 32; for( i = 0; i < truncj; i++ )( j = i/2; if( «(int)((i+l)/2)) & 1) > 0 ) sign = -1; else sign = 1 ; tempfi] = datajnfj] + sign*datajn[j+16]; for( i = 0; i < truncj; i++ ) trans_out[i] = tempfi]; void one_d_wt_64( datajn, trunc_l, uans_out ) float *datajn; /* datajn: 1-D data array in.*/ int truncj; /* uauncj: size of transform coefficients to be computed.*/ float *uans_out; /* tians_out: 1-D transform coefficient array out.*/ { float temp[64]; int truncjO, i, j, sign; truncjO = (truncj- 1) / 2 + 1; one_d_wt_32( datajn, truncjO, datajn ); one_d_wt_32( (data jn+32), truncjO, (data jn+32) ); if( truncj > 64 ) truncj = 64; for( i = 0; i < truncj; i++ ){ j = i 2; if( (((int)((i+l)/2)) & 1) > 0 ) sign = -1; else sign = 1 ; tempfi] = datajnfj] + sign*data jnfj+32]; 1 for( i = 0; i < truncj " ; i++ ) trans_out[i] = tempfi]; } void one_d_wt( data_in, size, trunc_l, trans_out ) float *da _in; /* data_in: 1-D data array in. + / int size; /* size: size of the I-D data aπay.*/ int truncj; /* tfauncj: size of transform coefficients to be computed.*/ float *uans_out; /* uans_out: 1 -D transform coefficient array out.*/ { switch (size) { case 2: one_d_wt_2( datajn, truncj, trans_out ); break; case 4: one_d_wt_4( datajn, truncj, uans_out ); break; case 8: one_d_wt_8( datajn, truncj, uans_out ); break; case 16: one_d_wt_16( datajn, truncj, trans_out ); break; case 32: one_d_wt_32( datajn, truncj, trans_out ); break; case 64: one_d_wt_64( datajn, truncj, trans_out ); break; default: printfC'Walsh Transform uses size 2, 4, 8, 16, 32 or 64 here\n"); break; } /*one_d_wt c.c: subroutine to perform single step fast 1-D RECURSIVE Walsh Transform. Copyright by Xiaonong Ran */ void one_d_wt_2 c( data_inl, data_in2, truncj, tians_out ) float ♦ datajnl, ♦ datajn2; / ♦ Two 1-D data sub-arrays in.*/ int truncj; /* trauncj: size of transform coefficients to be computed.*/ float ♦ uans_out; / ♦ trans_out: 1 -D transform coefficient array out.*/ { float temρ[2]; if( truncj >= 2 ){ tempfO] = datajn 1[0] + datajn2[0]; tempfl] = datajnl [0] - data_in2[0]; uans_out[0] = tempfO]; uans__outfl] = tempfl]; } else if( trunc_l == 1 ){ trans_out[0] = datajn 1 [0] + data_in2[0]; void one_d_wt_4_rc( data_inl , data_in2, trunc_l, uans_out ) float ♦ datajnl , ♦ datajn2; /* Two 1 -D data sub-aπays in.*/ int truncj; /* tiauncj: size of transform coefficients to be computed.*/ float *uans_out; /* uans_out: 1 -D transform coefficient aπay out*/ float temp[4]; if( trunc_l >= 4 ){ tempfO] = datajn 1 [0] + datajn2[OJ; tempfl] = datajn 1 [0] - data_in2[0]; temp[2] = datajnl [1] - datajn2[l]; tempf3] = datajnl f l] + datajn2[ l]; trans_outfO] = tempfO]; uans_out[l] = tempfl]; trans_out[2] = temp[2]; uans_out[3] = tempf3]; ) else if( trunc_l == 3 ) { tempfO] = datajnl [0] + datajn2f0]; tempfl] = datajn If 0] - data_in2[0]; temp[2] = datajnlfl] - data_in2[l]; uans_out[0] = tempfO]; uans_outf l] = tempf l]; trans_out[2] = temρ[2]; } else if( trunc_l == 2 ) { tempfO] = data_in 1 [0] + datajn2[0] ; tempfl] = datajnl [0] - data_in2[0]; trans_out[0] = tempfO]; uans_out[l] = tempfl]; } else ift trunc_I = 1 ){ tempfO] = datajn 1 [0] + datajn2[0]; trans_out[0] = tempfO]; } } void one_d_wt_8 c( data_inl, data_in2, trunc_l, trans_out ) float *datajnl, *datajn2; /* Two 1-D data sub-arrays in.*/ int truncj; /* trauncj: size of transform coefficients to be computed.*/ float *uans_out; /* trans jmt: 1-D transform coefficient array out.*/ { float temp[8]; int i, j, sign; if( truncj > 8 ) truncj = 8; for( i = 0; i < truncj; i++ ){ j = i 2; if( (((int)((i+l)/2)) & 1 ) > 0 ) sign = -1 ; else sign = 1 ; tempfi] = datajnl [j] + sign*datajn2[j]; } for( i = 0; i < trunc_l; i++ ) trans_out[i] = tempfi]; void one_d_wt_16_rc( datajnl, datajn2, trunc_l, trans_out ) float *data_inl , *datajn2; /* Two 1 -D data sub-aπays in.*/ int truncj; /* uauncj: size of transform coefficients to be computed.*/ float ♦ trans_ ut; /* uans_out: 1-D transform coefficient array out*/ { float tempf l 6]; int i, j, sign; if( truncj > 16 ) truncj = 16; for( i = 0; i < truncj; i++ ){ j = i 2; if( (((int)((i+l)/2)) & 1) > 0 ) sign = -1; else sign = 1; tempfi] = datajn l fj] + sign*datajn2[j]; } for( i = 0; i < truncj; i++ ) trans_out[i] = tempfi]; void one_d_wt_32 c( datajnl, datajn2, truncj, trans_out ) float *datajnl, *data jn2; /* Two 1-D data sub-arrays in.*/ int truncj; /* traunc j: size of transform coefficients to be computed.*/ float *trans_out; /* trans_out: 1-D uansform coefficient array out.*/ { float temρ[32]; int i, j, sign; if( truncj > 32 ) truncj = 32; for( i = 0; i < truncj; i++ ){ j = i 2; if ( (((int)((i+ 1 )/2)) & 1 ) > 0 ) sign = - 1 ; else sign = 1 ; tempfi] = datajnl [j] + siεn*datajn2[j]; } for( i = 0; i < truncj; i++ ) trans_out[i] = tempfi]; void one_d_wt_64_rc( datajnl , dat jn2, truncj, trans_out ) float ♦ data_ml, ♦ datajn2; /* Two 1-D data sub-arrays .*/ int trunc_l; /* traunc_l: size of uansform coefficients to be computed.*/ float *trans_out; /* uans_ ut: 1-D transform coefficient array out*/ ( float temp [64]; int l, j, sign; ιf( truncj > 64 ) truncj = 64; for( l = 0; i < truncj; ι++ ){ J = i 2; ιf( (((ιnt)((ι+l)/2)) & 1 ) > 0 ) sign = -1 ; temp[ι] = da ijnl fi] + sιgn*datajn2[j]; for( i = 0; l < truncj; ι++ ) tjans_out[ι] = tempfi]; void one_d_wt c( datajnl, data_m2, size, truncj, trans_out ) float *data_ml, *datajn2; /* Two 1-D data sub-arrays in.*/ int size; /* size: size of the 1-D data array.*/ int truncj; /* frauncj: size of transform coefficients to be computed.*/ float *uans_out; /* uans_out: 1 -D transform coefficient array out*/ { switch (size) { case 2: one_d_wt_2_rc( datajnl, datajn2, truncj, trans_out ); break; case 4: one_d_wt_4 c( dataj l, datajn2, truncj, Uans_out ); break; case 8: one_d_wt_8 c( data_ιnl, datajn2, truncj, uans_out ); break; case 16: one_d_wt_16 c( datajnl, datajn2, truncj, trans_out ); break; case 32: one_d_wt_32_rc( datajnl, datajn2, truncj, trans_out ); break; case 64: one_d_wt_64_rc( datajnl, datajn2, truncj, Uans_out ); break; default: pnntfC'Walsh Transform uses size 2, 4, 8, 16, 32 or 64 here\n"); break; /*output_bits.c: subroutine to output binary bits. Copyright by Xiaonong Ran */ void output_bits( fp_out, buffer_output, bits_to_out, code, length ) FILE *fp_out; int ♦ buffer .utput, *bits_to_out, code, length; int i, itemp, outjemp; itemp = code; itemp «= (32-length); for( i = 0; i < length; i++ ){ (*buffer_output) »= 1; if( (itemp & 0x80000000) ) (*buffer_output) 1= 0x80; (*bits_to_out) -= 1; itemp «= 1; if( *bits o_out = 0 ){ outjemp = *buffer_output; /*Output buffer if it is*/ ρutc(out_temp,fp_out); /* now full. */ *bits_to_out = 8; } } /*qtwt_grow_costt.c: subroutine to generate the balanced quadtree in performing Walsh Transform Quaduee decomposition for all Nt Copyright by Xiaonong Ran */ void qtwt_grow_costt( frame,row,column,nn,mm,trunc,costt,wtt ) short ♦♦ frame; /* the current (MCP) frame. */ float ♦♦♦♦ costt; /* uee of merging-cost: index 1,2: root-blocks; index 3: levels of quad-trees, bottom-up; index 4: nodes ♦ / float ****** w tt; / ♦ uee of Walsh transform coefficients: index 1,2: root-blocks; index 3: levels of quad-trees, bottom-up; index 4: nodes index 5,6: coefficient block */ mt row, column, /* frame sizes */ mt mm, nn, /* mm (nn): the size of the smallest leaf (root) block. mm must be larger than size of truncated uansform blocks*/ int trunc; /* trunc: the size of truncated transform blocks.*/ { int l, j, j l, j2, k, 11, 12, 11 Jog, mm2, mm3; int al, a2, bl, b2, cl, c2, cv, cq, trunc2, float temp, **temp_2d; short *qt_codet; /* temperary memory for qt_code */ c_nn = column / nn; II = nn/mm; 11 Jog = (int) ( log2((double)ll) + 0.5 ); /* number of stages after root for the quaduee*/ 12 = 11 *11 ; /*number of possible leaf nodes and the size of tran_v*/ k = (12-1./3; /*sιze of the quadtree code*/ trunc2 = 2*trunc; ιf( k > 0 ) ιf( (qt_codet = (short *) calloc( k, sιzeof(short)))==NULL ){ fρπntf( stderr, "wc: no more memory\n" ); exιt( 0 ); ιf( (temρ_2d = (float **) calloc( 2*mm, sιzeof(float *)))==NULL ){ fρπntf( stdeπ, "wc: no more memory\n" ); exιt( 0 ); ) for( i = 0; l < 2*mm; ι++ ) ιf( (temp_2dfι] = (float *) calloc( 2*mm, sizeoftfloat )))=NULL){ fpπntf( stdeπ, "wc: no more memory\n" ); exιt( 0 ); for( u = 0; u < rjin; iι++ ) for( j) = 0; j < c_nn; jj++ ){ /* put uansf. block of the basic blocks an 1-D array in Z-scan order. */ for( l = 0; ι < 12; ι++ ){ jl = 0; . 2 = 0; for( j = 0; j <= HJog; j++ ){ jl += ( (ι»(2* +l))&l )«j; 2 += ( (ι»(2*j))&l )«j; for( al = 0; al < mm; al++ ) for( a2 = 0; a2 < mm; a2++ ) temp_2d[al][a2] = frame[ϋ*nn+jl*mm+al][jj*nn+j2*mm+a2]; two_d_wt( temp_2d, mm, mm, trunc, trunc, wtt[ii]fjj][0][i] ); /* construct the second last level of the quaduee, (die last level are all leafs).*/ mm2 = mm*mm*mm + mm* 16; mm3 = ~ *2; for( j = 0; j < 12/4; j++ ){ for( al = 0; al < tr_nc2; al++ ) for( a2 = 0; a2 < trunc2; a2++ ) temp_2d[al][a2] = 0.0; two_d_wtjc_li(wtt[ii][jj][0][j*4],wtt[ii][jj][0][j*4+l], wtt[ii][jj][0]fj*4+2], wtt[ϋ][iJ][0][j*4+3], mm3, mm3, Uunc2, u c2, temp_2d ); temp = 0.0; for( al = 0; al < trunc2; al++ ) for( a2 = 0; a2 < trunc2; a2++ ) if( al >= trunc II a2 >= trunc ) temp += temp_2d[al][a2]*temp_2dfal][a2]; temp /= (float)mm2; /* divide by 4*(2*mm)**2 (2nd stage)*/ costt[ii]fjj][0][j] = temp; if( 0==0 ){ qt_codet[j] = 0; for( al = 0; al < trunc; al++ ) for( a2 = 0; a2 < trunc; a2++ ) wtt[ii][jj]fl][j][al][a2] = temp_2dfal][a2]; ) } bl = 0; /* store the starting and ending points of this level*/ b2 = j; /* of quadtree code. */ /* construct all the upper levels of the quaduee. */ cl = 16; for( i = 11 Jog-2; i >= 0; i- ){ c2 = cl/4; mm2 *= 16; mm3 *= 2; for( j = 0; j < 12/cl; j++ ){ if( qt_codet[j*4+bl] == 0 && qt_codet|j*4+bl+l] — 0 && qt_codet[j*4+bl+2] == 0 && qt_codet[j*4+bl+3] = 0 ){ for( al = 0; al < trunc2; al++ ) for( a2 = 0; a2 < trunc2; a2++ ) temp_2d[al][a2] = 0.0; two_d_wt c_li( wtt[ii]fjj][ll jog-l-i][j*4], wtt[ii][jj][πjog-l-i]fj +l],wtt[ii][jj][njog-l -i][j*4+2], wtt[ϋ][jj][l lJog-l-i][j +3],mm3,mm3,trunc2,trunc2,temp_2d); temp = 0.0; for( al = 0; al < trunc2; al++ ) for( a2 = 0; a2 < trunc2; a2++ ) if( al >= trunc II a2 >= trunc ) temp += temp_2d[al][a2]*temp_2d[al][a2]; temp /= (float)mm2; costt[ii][jj][llJog-l -i][j] = temp*cl/4.0; /*divide by 4*(4*mm)**2 for 3rd stage*/ / ♦ divide by 4*(8*mm)**2 for 4th stage*/ / ♦ divide by 4*(16*mm)**2 for 5tb stage*/ if( 0==0 ){ qt_codet[b2+j] = 0; for( al = 0; al < trunc; al++ ) for( a2 = 0; a2 < uunc; a2++ ) wtt[ii]fjj]f]lJog-i][j][al][a2] = temp_2d[al][a2]; bl = b2; b2 += j; cl *= 4; if( k > 0 ) free( qt_codet ); for( i = 0; i < 2*mm; i++ ) free(temρ_2d[i]); free(temp_2d); / ♦ qtwt_prune_costt.c: subroutine to prune the balanced quaduee in performing Walsh Transform Quaduee decomposition for all Nt Copyright by Xiaonong Ran ♦ / void qtwt_prune_costt( row,column,nn,mm,costt,lnn,mse,step_size,uιreshold ) float ♦♦♦♦ costt; /* tree of merging-cost: index 1,2: root-blocks; index 3: levels of quad-uees, bottom-up; index 4: nodes */ int row, column; /* frame sizes */ int mm, nn; /* mm (nn): the size of the smallest leaf (root) block. mm must be larger than size of truncated uansform blocks*/ int Inn; / ♦ the target number of leaf-nodes.*/ double *mse; /* mean-squared-eπor of pruning. "7 float steρ_size; /* quantization step size for compute threshold. */ float threshold; /* threshold for pruning cost. */ ( int r in, cjin, ii, jj, nf, nff; int i. j. i3, j3. k3, jj3, j l , j2, k. 11, 12, I I jog; int al , a2, b3; float temp, tempi, factor; factor = 4*mm*mm; cjin = column / nn; 11 = nn/mm; 12 = 11 *11 ; / ♦ number of possible leaf nodes and the size of uan_v*/ 11 Jog = (int) ( log2((double)ll) + 0.5 ); /* number of stages after root for the quaduee*/ *mse = 0.0; for( i = 0; i < row/nn; ++i ){ for( j = 0; j < column/nn; ++j ){ ii = 12 / 4; for( k = 0; k < 11 Jog; ++k ){ for( jj = 0; jj < ii; ++jj ){ if( k == 0 && costt[i][j][k][jj]<threshold ){ *mse += costtfi][j]fk][jj]; costt[i][j]fk]_jj] = -costt[i][j]fk]fjj]-1.0; } else if( k > 0 && ( costt[i][j][k-l][_ύ*4] < 0 && costt[i][j][k-l][jj^4+l]<0 && costtfi][j][k-l][ip4+2]<0 && costt[i][j][k-l][jjM+3]<0 ) ){ temp = costt_i]_j]Ck][jj]; if( temp < threshold ){ ♦ mse += costt[i][j][k][jj]; costt[i][j][k][jj] = -costt[i]fj][k][jj]-1.0; } } ) ii /= 4; } } } ♦ mse ♦ = (4.0*mm*mm (float)(row*column)); 1 / ♦ qtwt_quan_deco2D.c: subroutine to input bits, to variable length decode them and to reconstruction frame; for Nt = 2; Copyright by Xiaonong Ran */ #include "bits o_matrix2D.c" void qtwt_quan_deco2D ( frame,step_size,row,column,nn,mm,trunc,fp_in,seq_to_2d ) short **frame, **seq o_2d; /* the current (MCP) frame */ int row, column; /* frame sizes */ int mm, nn; /* mm (nn): the size of the smallest leaf (root) block. mm must be larger than size of truncated Uansform blocks*/ int trunc; / ♦ trunc: the size of truncated transform blocks.*/ float step_size; /* quantization step size. */ float **temp_2d; short *length, *code; int i, j, k, ikk, ik, rjin, cjin, 11, 11 Jog, 12, ii, jj, flagl ; int bufferjnput, bitsjojnput, itemp, i2, ii3, jj3, al, a2, nn2; struct entry ♦ ueeh, ♦ uee_builder; float nn4, ♦♦ init_v; / ♦ initial value of DPCM of (0,0)th coef; may extended to other coef.s ♦ / float **costt; /* index 1: levels of quad-uees, bottom-up; index 2: nodes */ double sz jactor; /*sz_factor: step size factor. */ /********* jgjjjr . 2D arrav for blocks ************************************ if( (temp_2d = (float **) calloc( nn, sizeof(float *)))==NULL ){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < nn; i++ ) if( (temp_2d[i] = (float *) calloc( nn, sizeof(floaf)))=NULL){ fρrintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } /****#**** codes and lenεths for trunc=2 ********************************/ if( (code = (short *) calloc( 18, sizeof(short)))==NULL ){ fρrintf( stderr, "wc: no more memory\n" ); exit( 0 ); } if( (length = (short *) calloc( 18, sizeof(shoιt)))=NULL ){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } code[0]=l; lengthf0]=2; /* EOB */ code[l]=0; length[l]=3 */ code[2]=l; length[2]=l */ code[3]=2; length[3]=4: */ code[4]=7; length[4]=5; /* +-3 */ code[5]=24; length[5]=7; code[6]=50: length[6]=8; codef7]=26; length[7]=7; code[8]=54: length[8]=8; code[9]=103: length[9]=9; codef 10]=55: length[10]=8; codef 11]=204: lengthf l 1]=10 codefl2]=41 1 ; lengthfl 2]= 11 code[13]=821 ; lengthf l 3]= 12 codef 14]=3282; length [14]= 14: codef 15]= 1640; length [15]= 13: codef 16]=6567; length[16]=15 codef 171=6566; lengthfl 7]= 15 /**#****************** building the huffman uee **************************/ if((treeb=( struct entry *) calloc( 1, sizeof(struct entry)))=NULL) { fprintf( stdeπ, "wc: no more memory \n" ); exit( 0 ); for( i = 0; i < 18; i++ ){ tree_builder = treeh; ikk = codefi]; ikk «= (32-length[i]); for( ik = 0; ik < lengthfi]; ik++ ){ if( (ikk & 0x80000000) ){ if( uee_builder->leaf 1 = 0 ) if((tree_builder->leaf]=(s_ruct entry *) calloc(l,sizeof(struct enfry)))==NULL){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } treejjuilder = U"ee _builder->leaf 1 ; else { if( tree_builder->leafO = 0 ) if((tree_builder->leafO=(struct entry *) calloc(l,sizeof(sfruct enfry)))==NULL){ fprintf( stderr, "wc: no more memory\n" ); exit( 0, ); tree_builder = free_builder->leaf0; } ikk «= 1 ; } tree_builder->flag_node = 1 ; tree_builder->index = i; /********************* en( j of building the huffman tree *******************/ some size-parameters r_nn = row / nn; c_nn = column / nn; 11 = nn/mm; 12 = 11 *11 ; / ♦ number of possible leaf nodes and the size of Uan_v^/ 11 Jog = (int) ( log2((double)l l) + 0.5 ); /* number of stages after root for the quaduee.*/ bitsjojnput = 0; /************************************************************************** ******************* one sinule-uee ************************************** if((costt=(float **)calloc(ll Jog,sizeof(float *)))=NULL){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); ii = 12 / 4; for( k = 0: k < 11 Jog; ++k ){ if((costt[k]=(float *)calloc(ii,sizeof(float)))=NULL) { fρrintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } ii /= 4; } for( i = 0; i < r_nn; ++i ){ for( j = 0; j < c_nn; ++j ){ ii = 1 ; for( k = 11 Jog-1; k >-l; k- ){ /* input quadtree suucture */ for( jj = 0; jj < ii; ++jj ){ if( k -= 11 jog-1 II costt[k+l]f(int)(jj/4)] > 0 ){ if( bitsjojnput = 0 ){ /* Read the next byte if*/ bufferjnput = getc( fpjn ); / ♦ bits are left in buffer*/ bits_to_input = 8; ) if( (bufferjnput & 1) ) costt[k][jj] = 1.0; else costt[k][jj] = -1.0; bufferjnput »= 1 ; bitsjojnput -= J; } else costt[k]fjj] = -1; } ii *= 4; } /* end of outputing quadtree */ ii = 12; /* input codes of WT coefficients */ nn4 = mm*mm; nn2 = mm; sz actor = 1.0; for( k = 0; k <= 11 Jog; ++k ){ for( jj = 0; jj < ii; ++jj ){ if( (k == 0 II costt[k-l]fjj]< 0) && ( k== 11 Jog II costt[k][(int)(jj/4)] >= 0 ) ){ if( flagl == 0 ){ itemp = 0; for( i2 = 0; i2 < 24; i2++ ){ if( bitsjojnput = 0 ){ bufferjnput = getc( fp_in ); bitsjojnput = 8; ) itemp «= 1; if( bufferjnput & 1 ) itemp += 1 ; buffer_input »= 1 ; bitsjojnput -= 1; } temρ_2d[0][0] = itemp; init_v[0][0] = itemp/nn4; } bits_to_matrix2D( temp_2d, init_v, &flagl, fpjn, code, length, (steρ_size/sz jactor), nn4, trunc, &buffer jnput, &bitsjo jnput, treeh ); two_d_iwt( temp_2d, nn2, nn2, frunc, frunc, temp_2d ); ii3 = i*nn + seq_to_2d[jj][0]*nn2; jj3 = j*nn + seqjo_2d[jj][l]*nn2; for( al = 0; al < nn2; al++ ) for( a2 = 0; a2 < nn2; a2++ ) frame[ii3+al][jj3+a2] = temp_2d[al][a2]; } } ii /= 4; nn4 *= 4; nn2 *= 2; sz jactor *= 2.0; if( step_size/sz actor < 1.0 ) szjactor = step_size; } } } for( i = 0; i < nn; i++ ) free( temp_2d[i] ); free( temp_2d); for( k = 0; k < 11 Jog; ++k ) free( costtfk] ); free( costt ); } /*qtwt_quan_enco2D.c: subroutine to perform quantization and variable length encoding; for Nt = 2; include "output_bιts.c" Copyright by Xiaonong Ran */ #ιnclude "outputjndex2D.c" void qtwt_quan_enco2D( step_size,row,column,nn,mm,trunc,costtwtt,fp_out ) int row, column; /* frame sizes */ mt mm, nn; /* mm (nn): the size of the smallest leaf (root) block. mm must be larger than size of truncated uansform blocks*/ int trunc; /* uunc: the size of truncated uansform blocks.*/ float step_sιze; /* quantization step size. */ float ****costt; /* uee of mergmg-cost: index 1,2: root-blocks; index 3: levels of quad-trees, bottom-up; index 4: nodes */ float ****** w tt; /* tree of Walsh transform coefficients: index 1,2: root-blocks; index 3: levels of quad-tiees, bottom-up; index 4: nodes index 5,6: coefficient block */ FILE *fp_out; { short *length, *code; int buffer jutput bitsjo_out ♦♦ indexx; float nn4, ♦♦ init_v; /*iniϋal value of DPCM of (0,0)th coef; may extended to other coef.s */ int i, j, k, r_nn, cjin, 11, 12, 11 Jog, ii, jj, itemp, flagl; int al, a2, kk, fO, i6, j6, k6, il, i7; double temp, sz jactor; /*sz jactor: step size factor. */ float bits_uee, leaf_num, quan_freq[514], entropy; FILE *fp jq_out, *fopen(); /**** initiate counter and memory for computing entropy, etc. ***********/ bιts_tree = 0; for( i = 0; i < 514; i++ ) quan jreqfi] = 0; ************************************************************************ /********* initiate output buffer and counter ***************************/ buffer_outρut = 0; bits to_out = 8; /************************************************************************/ ; ********* nodes and lengths for trunc=2 ********************************/ if( (code = (short *) calloc( 18, sizeof(short)))==NULL ){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } if( (length = (short *) calloc( 18, sizeof(short)))=NULL ){ fρrintf( stdeπ, "wc: no more memory\n" ); exιt( 0 ); code[0]=l ; length[0]=2; /* EOB*/ code[l]=0: lengthfl ]=3; 1*0*1 code[2]=l: length[2]=l; l*+-\ *l codef3]=2; length[3]=4; I* +-2*1 code[4]=7; length[4]=5; +-3*/ code[5]=24; length[5]=7; /* +-4*/ code[6]=50; lengthf6]=8; /* +-5*/ code[7]=26: length[7]=7; /* +-6,+-7 l lx */ code[8]=54; length[8]=8; /* +-8,+-9 lOOx*/ code[9]=103; length[9]=9; /* +-10, +-11 101x*/ codef 10]=55; length[ 10]=8; /* +-12 ... +-15 l lxx */ code[ l 11=204; lengthf l 1 ]= 10: /* +-16 ... +-19 lOOxx */ codef 12]=4H ; lengthfl 2]= 1 1 /* +-20 ... +-23 lOlxx */ codef l3]=821 ; lengthfl3]=12 /* +-24 ... +-27 l lOxx */ code[ 141=3282; length[14]=14 /* +-28 ... +-31 l l lxx */ code[15]=1640; length[15]=13 /* +-32 ... +-63 Ixxxxx */ code[ 161=6567; length[16]=15 /* +-64 ... +-127 I xxxxx */ codef 171=6566; length[17]=15 /* +-128 ... +-255 Ixxxxxxx */ * ************************************************************ ***********/ /********* array memory for matrix of code-index ************************/ if( (indexx = (int **) calloc( trunc, sizeof(int ♦ )))==NULL )( fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; l < trunc; i++ ){ if( (indexx [i] = (int ♦ ) calloc( Uunc, sizeof(int)))=NULL){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); /************************************************************************/ ****************** gome size-parameters *********************************/ r_nn = row / nn; cjin = column / nn; 11 = nn/mm; 12 = 11 *11; / ♦ number of possible leaf nodes and the size of tran_v*/ 11 Jog = (int) ( log2((double)ll) + 0.5 ); /* number of stages after root for the quaduee.*/ *************************************************** *********************** for( i = 0; i < rjin; ++i ){ for( j = 0: i < cjin; ++j ){ ii = l; for( k = 11 jog-1; k >-l; k- ){ /* output quaduee structure */ for( jj = 0; jj < ϋ; ++jj ){ if( k== 11 jog-1 && costt[i]fj][k]fjj] < 0 ){ ouφut_bits(fp_out&buffer_output&bits jo _out,0, 1 ); bits_tree += 1 ; ) else if( costt[i][j][k][jj) >= 0 ){ outρut_bits(fp_out,&buffer_output&bits_to_out, 1,1); bits_tree += 1; } else if( cos_t[i]fj][k][jj] < 0 && costt[i]fj][k+l][(int)(jj/4)]>=0 ){ output_bits(fp_out&buffer_output&bits_to_out,0,l); bits_tree += 1 ; } } ii *= 4; } /* end of outputing quaduee */ ii = 12; /* quantizing of WT coefficients */ nn4 = mm*mm; sz jactor = 1.0; for( k = 0; k <= 11 Jog; ++k ){ for( jj = 0; jj < ii; ++jj ){ if( (k == 0 II costt[i]fj][k-l][jj]< 0) && ( k== 11 Jog II costt[i][j]fk][(int)(jj/4)] >= 0 ) ){ for( al = 0; al < trunc; al++ ){ for( a2 = 0; a2 < trunc; a2++ ) if( step_size > 0 ){ temp = (wtt[i]fj][k]fjj][al][a2]/nn4+ (step_size/szjactor)/2.0)/(steρ_size/sz actor); if( temp >= 0 ) kk = (int)(temp); else kk = -(int)(-temp)-l; indexx[al]fa2] = kk; quan jreq[indexx[al][a2]+256] += 1; else printfCϋ! steρ_size=0 !!!\n"); /**************** z j zag scaning and encoding **************/ k6 = 0; i6 = 0; j6 = 0; f0 = 0; if( indexx [i6]fj6] == 0 ) fO = 1; else output_index2D( indexx[i6][j6], fp_out, code, length, &buffer_output, &bits_to_out ); while( i6 != trunc-1 II j6 != trunc-1 ){ if( i6 = 0 ){ j6++; k6++; if( indexx [i6]fj6] == 0 ) fO += 1 ; else { if( fO == 1 ){ f0 = 0; outρut_bits(fp_ouu&buffer_output&bits_to_out, code[l],length[l]); } else if( fO > 1 ){ for( i7=0; i7<f0; i7++ ) output_bits(fp_out&buffer_outρut,&bits_to_out, code[l],length[]]); f0 = 0; } output_index2D( indexx[i6][j6], fρ_out, code, length, &buffer_output, &bits_to_out ); } for( il = j6-l ; il > -1 ; il - )( j6-; i6++; k6++; if( indexx[i6]fj6] == 0 ) fO += 1 ; else { if( f0 == 1 ){ fO = 0; output_bits(fp_out&buffer_output,&bits o_out, codef I lengthfl]); J else if( fO > 1 ){ for( i7=0; i7<f0; i7++ ) outρut_bits(fp_out,&buffer_output&bits_to_out, code[l],length[l]); f0 = 0; } outputjndex2D( indexx[i6]fj6], fp_out, code, length, &buffer_output, &bits_to_out ); } } } else if( j6 = 0 && i6 < trunc-1 ){ i6++; k6++; if( indexx [i6][j6] == 0 ) rø += 1 ; else { if( O == 1 ){ f0 = 0; outρut_bits(fp_out,&buffer_output,&bitsJo_out, code[l],length[l]); } else if( fO > 1 ){ for( i7=0; i7<f0; i7++ ) output_bits(fp_out,&buffer_output,&bits_to_out, codef l],length[l]); f0 = 0; output_index2D( indexx[i6][j6], fp_out, code, length, &buffer_output, &bits_to_out ); for( il = i6-l; il > -1 ; il- ){ i6~; J6++; k6++; if( ιndexx[i6][j6] == 0 ) f() += 1 ; else { if( fO == 1 ){ f0 = 0; ouφut_bits(fp_out&buffer_output&bits o_out, codef l],length[l]); } else if( f0 > 1 ){ for( i7=0; i7<f0; i7++ ) output_bits(fp_out&buffer_output,&bits_to_out, code[ l],length[l]); f0 = 0; outputjndex2D( indexx[i6]fj6], fp_out, code, lengtii, &buffer_output, &bits_to_out ); } else if( i6 = uunc-1 ){ j6++; k6++; if( indexx[i6][j6] == 0 ) fO += 1; else { if( fO == l ){ f0 = 0; output_bits(fp_out,&buffer_outρut,-_bits_to_out, codefl],length[l]); } else if( fO > 1 ){ for( i7=0; i7<fl); i7++ ) output_bits(fp_out,&buffer_output,&bits_to_out, code[l],length[l]); f0 = 0; } ouφut_index2D( indexx[i6][j6], fp_out, code, length, &buffer_outρut, &bits_to_out ); } for( il = j6+l; il < Uunc; il++ ){ i6-; j6++; k6++; if( indexx[i6][j6] == 0 ) fO += 1; else { if( fO == 1 ){ f0 = 0; ouφut_bits(fρ_out,&buffer_ouφut,&bitsJo_out, code[l],length[l]); } else if( fO > 1 ){ for( i7=0; i7<f0; i7++ ) ouφut_bits(fp_out,&buffer_output,&bitsjo_out, code[l],length[l ]); fO = 0; } output_index2D( indexx[i6][j6], fp_out, code, length, &buffer_outρut, &bits_to_out ); else if( j6 = trunc-1 ){ 10 i6++; k6++; ιf( indexx[i6](j6] == 0 ) fO += 1 ; else { if( ft) == 1 ){ fO = 0; 15 output_bits(fρ_out&buffer_outρu_,&bitsjo_out, codef l],length[l]); ) else if( fO > 1 ){ for( i7=0; i7<f0; i7++ ) 20 outρut_bits(fp_out,&buffer_outρut&bits_to_out, codefl],length[l]); fO = 0; } output_index2D( indexx[i6][j6], fp_out, code, length, 25 <__buffer_output, &bits_to_out ); } for( il = i6+l; il < trunc; il++ ){ i6++; j6~; k6++; if( indexx[i6]fj6] == 0 ) fO += 1; 3 0 else { iff fO == 1 ){ f0 = 0; output_bits(fp_out,&buffer_ouφut,&bits_to_out, code[l],lengtb[l]); 35 } else iff fO > 1 ){ for( i7=0; i7<f0; i7++ ) ouφut_bits(fp_out,ι_-buffer_ouφu_,_-bits o_out, code[l],length[l]); 40 10 = 0; } ouφut_index2D( indexx[i6]fj6], fp_out, code, length, &buffer_output, &bits_to_out ); } 45 } iff f0 > 0 && truno 1 ){ output_bi s(fp_out,&buffer_ouφut,&bits_to_out, 50 codef0],length[0]); quan jreq[0+256] -= fO; /* subsuact the counts for 0's in EOBs */ quan_freq[0] += 1 ; } /********** end of zigzag scaning and encoding ***************/ ii /= 4; nn4 *= 4; szjactor *= 2.0; iff step_size/sz actor < 1.0 ) szjactor = step_size; iff bitsjo_out < 8 ){ buffer_outρut »= bits_to_out; i = buffer_output; /*Output die last byte. */ putc(i,fp_out); for( i = 0; i < 514; i++ ) leaf_num += quan jreqfi]; entiopy = 0.0; for( i = 0; i < 514; i++ ){ iff quan jreqfi] > 0 ){ quan jreqfi] /= leafjium; enuopy -= quan jreq[i]*log2((double)quan jreq[i]); printfC'entropy bytes= %f\n", (entropy*leaf_num+bits_uee)/8.0 ); for( i = 0; i < trunc; i++ ) free( indexxfi] ); free(indexx); free( code ); free( length ); /*two_d_wtc: subroutine to perform complete fast recursive 2-D Walsh Transform. Copyright by Xiaonong Ran */ void two_d_wt( datajn, row_size, col_size, truncj, truncj:, uans_out ) float **data jn; /* 2-D data array in.*/ int row_size, col_size; /* row # and column # of the 2-D data array.*/ int truncj, trunc_c; /* row # and column # of trans, coeff. to be computed.*/ float **uans_out; /* 2-D uansform coefficient array out*/ ( float *temp; int i, j; iff row_size = 1 && col_size == 1 ) ( trans_out[0][0] = datajn f0][0]; return; iff (temp = (float *) calloc( col_size, sizeofffloat)).=NULL ){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < row_size; i++ ){ for( j = 0; j < co size; j++ ) tempfj] = datajnfi][j]; one_d_wt( temp, col_size, trunc_c, temp ); for( j = 0; j < trunc_c; j++ ) data_in[i][j] = tempfj]; } free( temp ); iff (temp = (float *) calloc( row_size, sizeof(float)))=NULL ){ fprintff stderr, "wc: no more memory\n" ); exit( O ); } for( i = 0; i < trunc_c; i++ ){ for( j = 0; j < row_size; j++ ) tempfj] = datajn[j][i]; one_d_wt( temp, row_size, truncj, temp ); for( j = 0; j < truncj; j++ ) trans_out[j][i] = tempfj]; free( temp ); /*two_d_wtc: subroutine to perform complete fast recursive 2-D Walsh Transform. Copyright by Xiaonong Ran */ void two_d_wt( datajn, row_size, coLsize, truncj, trunc_c, uans_out ) float **data_in; /* 2-D data array in.*/ int row_size, coLsize; /* row # and column # of the 2-D data array.*/ int truncj, trunc_c; /* row # and column # of trans, coeff. to be computed.*/ float **trans_out; /* 2-D transform coefficient array out*/ { float *temp; iff row_size = 1 && coLsize == 1 ) { trans )ut[0][0] = datajn [0][0]; return: iff (temp = (float *) calloc( coLsize, sizeof(float)))=NULL ){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < row_size; i++ ){ for( j = 0; j < coLsize; j++ ) tempfj] = datajn[i][j]; one_d_wt( temp, coLsize, trunc_c, temp ); for( j = 0; j < trunc_c; j++ ) datø_.in[i]fj] = tempfj]; free( temp ); iff (temp = (float *) calloc( row_size, sizeofffloat)))=NULL ){ fρrintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < truncj:; i++ ){ for( j = 0; j < row_size; j++ ) tempfj] = datajnfj][i]; one_d_wt( temp, row_size, truncj, temp ); for( j = 0; j < truncj; j++ ) uans_out[j][i] = tempfj]; free( temp ); /*two_d_wt c.c: subroutine to perform single step fast 2-D RECURSIVE Walsh Transform. Copyright by Xiaonong Ran */ void two_d_wt c_li( datajnlj, datajnl_2, data_in2_l, data_in2_2, row_size, coLsize, truncj, uunc_c, uans_out ) float **data_inl_l, **data_inl_2, **datajn2_l, **datajn2_2; /* Four 2-D data sub-arrays in.*/ int row_size, coLsize; /* row # and column # of the 2-D data array.*/ int truncj, trunc_c; /* row # and column # of trans, coeff. to be computed.*/ float **trans_out; /* 2-D transform coefficient array out.*/ float *templ, *temp2, ♦ temρ_out, ♦♦ temp_outl, **temp_out2; int i, j, trunc jϋ, frunc_c0; trunc jO = ( trunc -D/2+1; trunc_cO = (trunc_c-l)/2+l ; iff truncj = 0 ) truncjO = 0; iff trunc_c = 0 ) trunc_cO = 0; iff (tempi = (float *) calloc( trunc_c0, sizeof(float)).==NULL ){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } iff (temp2 = (float *) calloc( trunc_c0, sizeofffloat)))==NULL ){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } iff (tempj tl = (float **) calloc( trunc_r0, sizeofffloat *)))==NULL ){ fprintff stdeπ, "wc: no more memory \n" ); exit( 0 ); 1 for( i = 0; i < truncjO; i++ ){ iff(temp .utl [i]=(float *)calloc( trunc_c, sizeofffloat)))=NULL){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); iff (temp_out2 = (float * ♦ ) calloc( trunc jϋ, sizeofffloat ♦ )))==NULL ){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < truncjO; i++ ){ iff(temp_out2[i]=(float ♦ )calloc( truncj:, sizeofffloat)))=NULL){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); for( i = 0; i < trunc_r0; i++ ){ for( j = 0; j < tπιnc_c0; j++ ) { tempi [j] = datajnl_l[i][j]; temp2fj] = datajn l_2fi][j]; } one_d_wt c( tempi, temp2, coLsize, truncj:, temp_outl[i] ); for( j = 0; j < trunc_c0; j++ ) { templfj] = datajn2_l[i][j]; temp2fj] = datajn2J>fi][j]; } one_d_wt c( tempi, temp2, coLsize, truncj:, temp_out2[i] ); free( tempi ); free( temρ2 ); iff (tempi = (float *) calloc( truncjO, sizeofffloat)))==NULL ){ fprintff stdeπ, "wc: no more memory \n" ); exit( 0 ); } iff (temp2 = (float *) calloc( trunc jO, sizeofffloat)))==NULL ){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); iff (temp_out = (float *) calloc( Uunc , sizeof(float)))=NULL ){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); for( i = 0; i < truncj ; i++ ){ for( j = 0; j < truncjO; j++ ) { templ fj] = temp_outl[j][i]; temp2[j] = temp_out2fj][i]; } one_d_wt c( tempi, temp2, row_size, Uuncj, temρ_out ); for( j = 0; j < trunc ; j++ ) trans_out[j][i] = temρ_out[j]; free( tempi ); free( temp2 ); free( temρ_out ); for( i = 0; i < truncjO; i++ ) free( temρj.utl[i] ); free( temp_outl ); for( i = 0; i < trunc_r0; i++ ) free( temp_out2fi] ); free( temρ_out2 ); void two_d_wt c( datajn, row_size, coLsize, truncj, truncj , frans_out ) float **data jn; /* 2-D data array in.*/ int row_size, coLsize; /* row # and column # of die 2-D data array.*/ int truncj, truncj:; /* row # and column # of trans, coeff. to be computed.*/ float **trans_out; /* 2-D transform coefficient array out*/ { int row_size0, coLsizeO, truncjO, frunc_c0; float **datalj . **datal_2, **data2_l, **data2_2; int i, j; row_size0 = row_size/2; coLsizeO = col_size/2; truncjO = (truncj- D/2+1; trunc_cO = (trunc_c- D/2+1; iff uunc_r = 0 ) truncjO = 0; iff trunc_c = 0 ) ttunc_c0 = 0; iff row_sιze >= 2 && coLsize >= 2 ) { iff.dataLl = (float **)calloc( row_size0, sizeofffloat *)))=NULL){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ): ) for( i = 0; i < row_size0; i++ ) { if((datal_l [i]=(float *)calloc(coLsizeO,sizeofffloat)))=NULL){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); iff(datal_2 = (float **)calloc( row_sizeO, sizeofffloat *)))=NULL){ fprintff stdeπ, "wc: no more memory \n" ); exit( 0 ); } for( i = 0; i < row_size0; i++ ){ iff(datal_2[i]=(float *)calloc(coLsizeO,s_zeofffloat)))-=NULL){ fprintf( stdeπ, "wc: no more memory\n" ); exit( 0 ); iff(data2_l = (float **)calloc( row_size0, sizeofffloat ♦ )))=NULL){ fprintf( stderr, "wc: no more memory\n" ); exit( 0 ); } for( i = 0: i < row_size0; i++ ) { iff(data2_l [i]=(float *)calloc(coLsizeO,sizeofffloat)))=NULL)( fprintff stderr, "wc: no more memory\n" ); exit( 0 ); } " ) iff(data2_2 = (float **)calloc( row_size0, sizeofffloat *)))=NULL){ fprintff stdeπ, "wc: no more memory\n" ); exit( 0 ); } for( i = 0; i < row_size0; i++ ){ if((data2_2[i]=(float *)calloc(coLsizeO,sizeofffloat)))=NULL) { fprintff stderr, "wc: no more memoryVn" ); exit( 0 ); } for( i = 0; i < row_size0; i++ ) for( j = 0; j < coLsizeO; j++ ){ dataLlfilfj] = datajn[i][j]; datal_2fi]fj] = datajn [i][j+col_size0]; data2_l[i]fj] = data_in[i+row_sizeO][j]; data2_2[i][j] = datajn[i+row_size0]fj+coLsize0]; } two_d_wt_rc(datal_l,row_size0,coLsize0,minc__O,trunc_c0,dataLl); two_d_wt c(datal_2,row_sizeO,coLsizeO,frunc_rO,trunc_cO,datal_2); two_d_ wt c(data2_ 1 ,row_sizeO,col_sizeO, trunc_r0,trunc_c0,data2_ 1 ) ; two_d_wt_rc(data2_2,row_sizeO,coLsizeO,tπιnc_rO,trunc__cO,data2_2); two_d_wt c_li( datal_l, datal_2, data2_l, data2_2, row_size, coLsize, truncj, uuncj , trans_out ); } else return;

Claims: I claim: 1. A method for uansmitting information, wherein the information includes a plurality of pieces of data each identifiable by a location on a two dimensional grid, the method comprising the steps of: selecting a series of partitions of the information, each partition in the series having a coπesponding integer I with N≤I≤M and containing ' non-intersecting blocks, each block in each partition having a corresponding rectangular area of die two dimensional grid and containing all pieces of data having locations within the corresponding rectangular area, wherein for each integer J with N≤J<M, each block in the partition coπesponding to J equals the union of four blocks in die partition corresponding to J+l ; selecting a set of disjoint blocks from the blocks contained in the series of partitions, wherein and there exist in the set of blocks a first block and a second block such that the number of pieces of information in the first block is greater than the number of pieces of information in the second block; and transmitting a series of digital signals representing Walsh uansform coefficients of each block that is in both the plurality of blocks. 2. A method for drawing an image which is represented by a quadtree code, die method comprising the steps of: storing a portion quaduee code in a memory, me quaduee code including values which indicate leaf nodes on levels of a quaduee and values which indicate Walsh transform coefficients coπesponding to the leaf nodes; identifying a leaf node from the portion of quadtree code; parsing me portion of the quaduee code to isolate embedded Walsh uansform coefficients which correspond to the leaf node; identifying, on a drawing medium, a block of pixels which corresponds to the leaf node; and performing an inverse Walsh uansformation on the isolate Walsh transform coefficient, wherein the dimension of the inverse Walsh transformation depends on the size of the block and the Walsh transform coefficients are treated as the top-left components of the of a matrix having the same size as the block; filling the pixels with colors as indicated by corresponding values of the inverse Walsh transformation. 3. The method of claim 2, wherein the step of filhng the pixels with color comprises filling the pixels with shades of gray. 4. The method of claim 2, wherein the drawing medium is a video display screen. 5. The method of claim 2, wherein the drawing medium is a sheet in a printer and the step of filling pixels comprises printing on die sheet.

Inventors: RAN XIAONONG, RAN, XIAONONG
Applicants: NAT SEMICONDUCTOR CORP, NATIONAL SEMICONDUCTOR CORPORATION
Application year: 1994
Main classification: H04N7
IPC codes: H03M7, H04N1, H04N7, H04N11